-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Dear Allin and Jack, Attached are my changes to modelprint.c, for the correct presenting of the p-values levels of acceptance legend, i.e. the * near the values. Please consider using that code or adapt to better style. I really think that the legend should appear. - --- Again I found probably old code remains, that in my view will never produce output. See below the references to MCFadden (there are more about pseudo-random generators): grep "McFadden" gretl/gui2/*.c gretl/gui2/model_table.c: /* McFadden */ gretl/gui2/model_table.c: "McFadden's pseudo-R-squared")); gretl/gui2/model_table.c: "McFadden's pseudo-$R^2$")); gretl/gui2/model_table.c: "McFadden's pseudo-R{\\super 2}")); Thanks, Hélio Guilherme /* * Copyright (c) by Ramu Ramanathan and Allin Cottrell * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 2 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111, USA. * */ /* modelprint.c */ #include "libgretl.h" #include "libset.h" #include "system.h" #include "texprint.h" #define NO_RBAR_SQ(a) (a == AUX_SQ || a == AUX_LOG || a == AUX_WHITE || a == AUX_AR) static int print_coefficients (const MODEL *pmod, const DATAINFO *pdinfo, PRN *prn); static void depvarstats (const MODEL *pmod, PRN *prn); static void print_rho_terms (const MODEL *pmod, PRN *prn); static void print_binary_statistics (const MODEL *pmod, const DATAINFO *pdinfo, PRN *prn); static void print_arma_stats (const MODEL *pmod, PRN *prn); static void print_arma_roots (const MODEL *pmod, PRN *prn); static void print_tobit_stats (const MODEL *pmod, PRN *prn); static void print_heckit_stats (const MODEL *pmod, PRN *prn); static void print_poisson_offset (const MODEL *pmod, const DATAINFO *pdinfo, PRN *prn); static void print_ll (const MODEL *pmod, PRN *prn); static char pvalue_level(const double pval); #define RTFTAB "\\par \\ql \\tab " #define XDIGITS(m) (((m)->ci == MPOLS)? GRETL_MP_DIGITS : GRETL_DIGITS) #define ordered_model(m) ((m->ci == LOGIT || m->ci == PROBIT) && \ gretl_model_get_int(m, "ordered")) #define binary_model(m) ((m->ci == LOGIT || m->ci == PROBIT) && \ !gretl_model_get_int(m, "ordered")) #define pooled_model(m) (m->ci == OLS && \ gretl_model_get_int(m, "pooled")) void model_coeff_init (model_coeff *mc) { mc->b = NADBL; mc->se = NADBL; mc->tval = NADBL; mc->pval = NADBL; mc->slope = NADBL; mc->show_pval = 1; mc->df_pval = 0; mc->name[0] = '\0'; } static void print_y_median (const MODEL *pmod, PRN *prn) { double m = gretl_model_get_double(pmod, "ymedian"); if (na(m)) { return; } if (plain_format(prn)) { pprintf(prn, " %s = %.*g\n", _("Median of dependent variable"), XDIGITS(pmod), m); } else if (tex_format(prn)) { char s[32]; tex_dcolumn_double(m, s); pprintf(prn, "%s & %s \\\\\n", I_("Median of dependent variable"), s); } else if (rtf_format(prn)) { pprintf(prn, RTFTAB "%s = %g\n", I_("Median of dependent variable"), m); } else if (csv_format(prn)) { pprintf(prn, "\"%s\"%c%.15g\n", I_("Median of dependent variable"), prn_delim(prn), m); } } static void depvarstats (const MODEL *pmod, PRN *prn) { if (pmod->ci == LAD) { print_y_median(pmod, prn); } if (na(pmod->ybar) || na(pmod->sdy)) { return; } if (plain_format(prn)) { pprintf(prn, " %s = %.*g\n", _("Mean of dependent variable"), XDIGITS(pmod), pmod->ybar); pprintf(prn, " %s = %.*g\n", _("Standard deviation of dep. var."), XDIGITS(pmod), pmod->sdy); } else if (tex_format(prn)) { char x1str[32], x2str[32]; tex_dcolumn_double(pmod->ybar, x1str); tex_dcolumn_double(pmod->sdy, x2str); pprintf(prn, "%s & %s \\\\\n %s & %s \\\\\n", I_("Mean of dependent variable"), x1str, I_("S.D. of dependent variable"), x2str); } else if (rtf_format(prn)) { pprintf(prn, RTFTAB "%s = %g\n", I_("Mean of dependent variable"), pmod->ybar); pprintf(prn, RTFTAB "%s = %g\n", I_("Standard deviation of dep. var."), pmod->sdy); } else if (csv_format(prn)) { pprintf(prn, "\"%s\"%c%.15g\n", I_("Mean of dependent variable"), prn_delim(prn), pmod->ybar); pprintf(prn, "\"%s\"%c%.15g\n", I_("Standard deviation of dep. var."), prn_delim(prn), pmod->sdy); } } static void garch_variance_line (const MODEL *pmod, PRN *prn) { const char *varstr = N_("Unconditional error variance"); double v = pmod->sigma * pmod->sigma; if (plain_format(prn)) { pprintf(prn, " %s = %.*g\n", _(varstr), GRETL_DIGITS, v); } else if (rtf_format(prn)) { pprintf(prn, RTFTAB "%s = %g\n", I_(varstr), v); } else if (tex_format(prn)) { char xstr[32]; tex_dcolumn_double(v, xstr); pprintf(prn, "%s & %s \\\\\n", I_(varstr), xstr); } else if (csv_format(prn)) { pprintf(prn, "\"%s\"%c%.15g\n", I_(varstr), prn_delim(prn), v); } } static int real_essline (const MODEL *pmod, double ess, double sigma, PRN *prn) { if (ess < 0) { if (plain_format(prn)) { pprintf(prn, _("Error sum of squares (%g) is not > 0"), ess); pputs(prn, "\n\n"); } return 1; } if (plain_format(prn)) { pprintf(prn, " %s = %.*g\n", _("Sum of squared residuals"), XDIGITS(pmod), ess); pprintf(prn, " %s = %.*g\n", _("Standard error of residuals"), XDIGITS(pmod), sigma); } else if (rtf_format(prn)) { pprintf(prn, RTFTAB "%s = %g\n", I_("Sum of squared residuals"), ess); pprintf(prn, RTFTAB "%s = %g\n", I_("Standard error of residuals"), sigma); } else if (tex_format(prn)) { char x1str[32], x2str[32]; tex_dcolumn_double(ess, x1str); tex_dcolumn_double(sigma, x2str); pprintf(prn, "%s & %s \\\\\n%s ($\\hat{\\sigma}$) & %s \\\\\n", I_("Sum of squared residuals"), x1str, I_("Standard error of residuals"), x2str); } else if (csv_format(prn)) { pprintf(prn, "\"%s\"%c%.15g\n", I_("Sum of squared residuals"), prn_delim(prn), ess); pprintf(prn, "\"%s\"%c%.15g\n", I_("Standard error of residuals"), prn_delim(prn), sigma); } return 0; } static int GMM_crit_line (const MODEL *pmod, PRN *prn) { if (plain_format(prn)) { pprintf(prn, " %s = %.*g\n", _("GMM criterion"), XDIGITS(pmod), pmod->ess); } else if (rtf_format(prn)) { pprintf(prn, RTFTAB "%s = %g\n", I_("GMM criterion"), pmod->ess); } else if (tex_format(prn)) { char xstr[32]; tex_dcolumn_double(pmod->ess, xstr); pprintf(prn, "%s & %s \\\\\n", I_("GMM criterion"), xstr); } else if (csv_format(prn)) { pprintf(prn, "\"%s\"%c%.15g\n", I_("GMM criterion"), prn_delim(prn), pmod->ess); } return 0; } static int essline (const MODEL *pmod, PRN *prn) { if (pmod->ci == GMM) { return GMM_crit_line(pmod, prn); } else { return real_essline(pmod, pmod->ess, pmod->sigma, prn); } } static int essline_original (const MODEL *pmod, PRN *prn) { double ess = gretl_model_get_double(pmod, "ess_orig"); double sigma = gretl_model_get_double(pmod, "sigma_orig"); if (na(ess) || na(sigma)) { return 1; } return real_essline(pmod, ess, sigma, prn); } static void rsqline (const MODEL *pmod, PRN *prn) { const char *plainrsq[] = { N_("Unadjusted R-squared"), N_("Uncentered R-squared") }; const char *texrsq[] = { N_("Unadjusted $R^2$"), N_("Uncentered $R^2$") }; const char *rtfrsq[] = { N_("Unadjusted R{\\super 2}"), N_("Uncentered R{\\super 2}") }; int ridx = 0; int adjr2 = 1; if (na(pmod->rsq)) { return; } if (!plain_format(prn) && pmod->ci == TSLS) { return; } if (NO_RBAR_SQ(pmod->aux) || na(pmod->adjrsq)) { adjr2 = 0; } if (gretl_model_get_int(pmod, "uncentered")) { ridx = 1; } if (plain_format(prn)) { pprintf(prn, " %s = %.*g\n", _(plainrsq[ridx]), XDIGITS(pmod), pmod->rsq); if (adjr2) { pprintf(prn, " %s = %.*g\n", _("Adjusted R-squared"), XDIGITS(pmod), pmod->adjrsq); } } else if (rtf_format(prn)) { pprintf(prn, RTFTAB "%s = %g\n", I_(rtfrsq[ridx]), pmod->rsq); if (adjr2) { pprintf(prn, RTFTAB "%s = %g\n", I_("Adjusted R{\\super 2}"), pmod->adjrsq); } } else if (tex_format(prn)) { char r2[32]; tex_dcolumn_double(pmod->rsq, r2); pprintf(prn, "%s & %s \\\\\n", I_(texrsq[ridx]), r2); if (adjr2) { tex_dcolumn_double(pmod->adjrsq, r2); pprintf(prn, "%s & %s \\\\\n", I_("Adjusted $\\bar{R}^2$"), r2); } } else if (csv_format(prn)) { pprintf(prn, "\"%s\"%c%.15g\n", I_(plainrsq[ridx]), prn_delim(prn), pmod->rsq); if (adjr2) { pprintf(prn, "\"%s\"%c%.15g\n", I_("Adjusted R-squared"), prn_delim(prn), pmod->adjrsq); } } } static void pseudorsqline (const MODEL *pmod, PRN *prn) { if (na(pmod->rsq)) { return; } if (plain_format(prn)) { pprintf(prn, " %s = %.*g\n", _("McFadden's pseudo-R-squared"), XDIGITS(pmod), pmod->rsq); } else if (rtf_format(prn)) { pprintf(prn, RTFTAB "%s = %g\n", I_("McFadden's pseudo-R{\\super 2}"), pmod->rsq); } else if (tex_format(prn)) { char r2[32]; tex_dcolumn_double(pmod->rsq, r2); pprintf(prn, "%s = %s \\\\\n", I_("McFadden's pseudo-$R^2$"), r2); } else if (csv_format(prn)) { pprintf(prn, "\"%s\"%c%.15g\n", I_("McFadden's pseudo-R-squared"), prn_delim(prn), pmod->rsq); } } static const char *aic_str = N_("Akaike information criterion"); static const char *bic_str = N_("Schwarz Bayesian criterion"); static const char *hqc_str = N_("Hannan-Quinn criterion"); static const char *tex_hqc_str = N_("Hannan--Quinn criterion"); static const char *aic_abbrev = N_("AIC"); static const char *bic_abbrev = N_("BIC"); static const char *hqc_abbrev = N_("HQC"); static void info_stats_lines (const MODEL *pmod, PRN *prn) { const double *crit = pmod->criterion; if (pmod->aux == AUX_SQ || pmod->aux == AUX_LOG || pmod->aux == AUX_WHITE || pmod->aux == AUX_AR) { return; } if (na(crit[C_AIC]) || na(crit[C_BIC]) || na(crit[C_HQC])) { return; } if (plain_format(prn)) { pprintf(prn, " %s (%s) = %.*g\n", _(aic_str), _(aic_abbrev), XDIGITS(pmod), crit[C_AIC]); pprintf(prn, " %s (%s) = %.*g\n", _(bic_str), _(bic_abbrev), XDIGITS(pmod), crit[C_BIC]); pprintf(prn, " %s (%s) = %.*g\n", _(hqc_str), _(hqc_abbrev), XDIGITS(pmod), crit[C_HQC]); } else if (rtf_format(prn)) { pprintf(prn, RTFTAB "%s = %g\n", I_(aic_str), crit[C_AIC]); pprintf(prn, RTFTAB "%s = %g\n", I_(bic_str), crit[C_BIC]); pprintf(prn, RTFTAB "%s = %g\n", I_(hqc_str), crit[C_HQC]); } else if (tex_format(prn)) { char cval[32]; tex_dcolumn_double(crit[C_AIC], cval); pprintf(prn, "%s & %s \\\\\n", I_(aic_str), cval); tex_dcolumn_double(crit[C_BIC], cval); pprintf(prn, "%s & %s \\\\\n", I_(bic_str), cval); tex_dcolumn_double(crit[C_HQC], cval); pprintf(prn, "%s & %s \\\\\n", I_(tex_hqc_str), cval); } else if (csv_format(prn)) { pprintf(prn, "\"%s (%s)\"%c%.15g\n", I_(aic_str), I_(aic_abbrev), prn_delim(prn), crit[C_AIC]); pprintf(prn, "\"%s (%s)\"%c%.15g\n", I_(bic_str), I_(bic_abbrev), prn_delim(prn), crit[C_BIC]); pprintf(prn, "\"%s (%s)\"%c%.15g\n", I_(hqc_str), I_(hqc_abbrev), prn_delim(prn), crit[C_HQC]); } } static void print_liml_equation_data (const MODEL *pmod, PRN *prn) { double lmin = gretl_model_get_double(pmod, "lmin"); int idf = gretl_model_get_int(pmod, "idf"); if (!gretl_model_get_int(pmod, "restricted")) { print_ll(pmod, prn); } #if 0 info_stats_lines(pmod, prn); #endif if (!na(lmin)) { pprintf(prn, " Smallest eigenvalue = %g\n", lmin); if (idf > 0) { double X2 = pmod->nobs * log(lmin); pprintf(prn, " %s:\n", _("LR over-identification test")); pprintf(prn, " %s(%d) = %g %s %g\n", _("Chi-square"), idf, X2, _("with p-value"), chisq_cdf_comp(X2, idf)); } else if (idf == 0) { pprintf(prn, " %s\n", _("Equation is just identified")); } } } static void print_arbond_AR_test (double z, int order, PRN *prn) { double pv = normal_pvalue_2(z); pputs(prn, " "); if (plain_format(prn)) { pprintf(prn, _("Test for AR(%d) errors:"), order); } else { pprintf(prn, I_("Test for AR(%d) errors:"), order); } if (tex_format(prn)) { char numstr[32]; tex_float_string(z, 4, numstr); pprintf(prn, " $z$ = %s & [%.4f]", numstr, pv); } else { pprintf(prn, " z = %g (%s %.4f)", z, (plain_format(prn))? _("p-value") : I_("p-value"), pv); } gretl_prn_newline(prn); } enum { AB_SARGAN, AB_WALD, J_TEST }; static void print_GMM_chi2_test (const MODEL *pmod, double x, int j, PRN *prn) { const char *strs[] = { N_("Sargan over-identification test"), N_("Wald (joint) test"), N_("J test") }; const char *texstrs[] = { N_("Sargan test"), N_("Wald (joint) test"), N_("J test") }; double pv; int df; if (j == AB_SARGAN) { df = gretl_model_get_int(pmod, "sargan_df"); } else if (j == AB_WALD) { df = gretl_model_get_int(pmod, "wald_df"); } else { df = gretl_model_get_int(pmod, "J_df"); } pv = chisq_cdf_comp(x, df); if (tex_format(prn)) { pprintf(prn, "%s: ", I_(texstrs[j])); pprintf(prn, "$\\chi^2(%d)$ = %g & [%.4f]", df, x, pv); } else if (plain_format(prn)) { pprintf(prn, " %s:", _(strs[j])); if (j == J_TEST) { pputc(prn, ' '); } else { pputs(prn, "\n "); } pprintf(prn, "%s(%d) = %g (%s %.4f)", _("Chi-square"), df, x, _("p-value"), pv); } else { pprintf(prn, " %s:", I_(strs[j])); if (j == J_TEST) { pputc(prn, ' '); } else { gretl_prn_newline(prn); pputs(prn, " "); } pprintf(prn, "%s(%d) = %g (%s %.4f)", I_("Chi-square"), df, x, I_("p-value"), pv); } gretl_prn_newline(prn); } static void print_GMM_test_data (const MODEL *pmod, PRN *prn) { double x; if (tex_format(prn)) { pputs(prn, "\\end{tabular}\n\n\\vspace{1ex}\n"); pputs(prn, "\\begin{tabular}{ll}\n"); } if (pmod->ci == GMM) { x = gretl_model_get_double(pmod, "J_test"); if (!na(x)) { print_GMM_chi2_test(pmod, x, J_TEST, prn); } return; } x = gretl_model_get_double(pmod, "AR1"); if (!na(x)) { print_arbond_AR_test(x, 1, prn); } x = gretl_model_get_double(pmod, "AR2"); if (!na(x)) { print_arbond_AR_test(x, 2, prn); } x = gretl_model_get_double(pmod, "sargan"); if (!na(x)) { print_GMM_chi2_test(pmod, x, AB_SARGAN, prn); } x = gretl_model_get_double(pmod, "wald"); if (!na(x)) { print_GMM_chi2_test(pmod, x, AB_WALD, prn); } } static void ladstats (const MODEL *pmod, PRN *prn) { double ladsum = gretl_model_get_double(pmod, "ladsum"); int utf = plain_format(prn); if (tex_format(prn)) { char x1str[32], x2str[32]; tex_dcolumn_double(ladsum, x1str); tex_dcolumn_double(pmod->ess, x2str); pprintf(prn, "%s & %s \\\\\n", I_("Sum of absolute residuals"), x1str); pprintf(prn, "%s & %s \\\\\n", I_("Sum of squared residuals"), x2str); } else if (csv_format(prn)) { pprintf(prn, "\"%s\"%c%.15g\n", I_("Sum of absolute residuals"), prn_delim(prn), ladsum); pprintf(prn, "\"%s\"%c%.15g\n", I_("Sum of squared residuals"), prn_delim(prn), pmod->ess); } else { pprintf(prn, " %s = %.*g\n", (utf)? _("Sum of absolute residuals") : I_("Sum of absolute residuals"), GRETL_DIGITS, ladsum); pprintf(prn, " %s = %.*g\n", (utf)? _("Sum of squared residuals") : I_("Sum of squared residuals"), GRETL_DIGITS, pmod->ess); if (utf) { int ladcode = gretl_model_get_int(pmod, "ladcode"); if (ladcode == 0) { pputs(prn, _("\nWarning: solution is probably not unique\n")); } } } } static void print_f_pval_str (double pval, PRN *prn) { int utf = plain_format(prn); if (utf || rtf_format(prn)) { if (pval < .00001) { pprintf(prn, " (%s < %.5f)\n", (utf)? _("p-value") : I_("p-value"), 0.00001); } else { pprintf(prn, " (%s = %.3g)\n", (utf)? _("p-value") : I_("p-value"), pval); } } else if (tex_format(prn)) { if (pval < .00001) { return; } else { char pstr[32]; tex_dcolumn_double(pval, pstr); pprintf(prn, "%s $F()$ & %s \\\\\n", I_("p-value for"), pstr); } } else if (csv_format(prn)) { pprintf(prn, "\"%s\"%c%g\n", I_("p-value"), prn_delim(prn), pval); } } static void panel_variance_lines (const MODEL *pmod, PRN *prn) { double ws2 = gretl_model_get_double(pmod, "within-variance"); double bs2 = gretl_model_get_double(pmod, "between-variance"); double theta = gretl_model_get_double(pmod, "gls-theta"); if (na(ws2) || na(bs2)) { return; } if (plain_format(prn)) { pprintf(prn, " %s = %g\n", _("'Within' variance"), ws2); pprintf(prn, " %s = %g\n", _("'Between' variance"), bs2); if (!na(theta)) { pprintf(prn, " %s = %g\n", _("theta used for quasi-demeaning"), theta); } } else if (tex_format(prn)) { char xstr[32]; tex_dcolumn_double(ws2, xstr); pprintf(prn, "$\\hat{\\sigma}^2_{\\varepsilon}$ & %s \\\\\n", xstr); tex_dcolumn_double(bs2, xstr); pprintf(prn, "$\\hat{\\sigma}^2_u$ & %s \\\\\n", xstr); if (!na(theta)) { tex_dcolumn_double(theta, xstr); pprintf(prn, "$\\theta$ & %s \\\\\n", xstr); } } else if (rtf_format(prn)) { pprintf(prn, RTFTAB "%s = %g", I_("'Within' variance"), ws2); pprintf(prn, RTFTAB "%s = %g", I_("'Between' variance"), bs2); if (!na(theta)) { pprintf(prn, RTFTAB "%s = %g", I_("theta used for quasi-demeaning"), theta); } } else if (csv_format(prn)) { char d = prn_delim(prn); pprintf(prn, "\"%s\"%c%.15g\n", I_("'Within' variance"), d, ws2); pprintf(prn, "\"%s\"%c%.15g\n", I_("'Between' variance"), d, bs2); if (!na(theta)) { pprintf(prn, "\"%s\"%c%.15g\n", I_("theta used for quasi-demeaning"), d, theta); } } } static void Fline (const MODEL *pmod, PRN *prn) { if (pmod->ifc && pmod->ncoeff <= 2) { if (plain_format(prn)) { pprintf(prn, " %s = %d\n", _("Degrees of freedom"), pmod->dfd); } else if (tex_format(prn)) { pprintf(prn, "%s & %d \\\\\n", I_("Degrees of freedom"), pmod->dfd); } else if (rtf_format(prn)) { pprintf(prn, RTFTAB "%s = %d\n", I_("Degrees of freedom"), pmod->dfd); } else if (csv_format(prn)) { pprintf(prn, "\"%s\"%c%d\n", I_("Degrees of freedom"), prn_delim(prn), pmod->dfd); } return; } if (plain_format(prn)) { char tmp[32]; sprintf(tmp, "%s (%d, %d)", _("F-statistic"), pmod->dfn, pmod->dfd); if (na(pmod->fstt)) { pprintf(prn, " %s %s\n", tmp, _("undefined")); } else { pprintf(prn, " %s = %.*g", tmp, XDIGITS(pmod), pmod->fstt); print_f_pval_str(f_cdf_comp(pmod->fstt, pmod->dfn, pmod->dfd), prn); } } else if (tex_format(prn)) { if (na(pmod->fstt)) { pprintf(prn, "$F(%d, %d)$ & \\multicolumn{1}{c}{\\rm %s} \\\\\n", pmod->dfn, pmod->dfd, I_("undefined")); } else { char x1str[32]; tex_dcolumn_double(pmod->fstt, x1str); pprintf(prn, "$F(%d, %d)$ & %s \\\\\n", pmod->dfn, pmod->dfd, x1str); print_f_pval_str(f_cdf_comp(pmod->fstt, pmod->dfn, pmod->dfd), prn); } } else if (rtf_format(prn)) { char tmp[32]; sprintf(tmp, "%s (%d, %d)", I_("F-statistic"), pmod->dfn, pmod->dfd); if (na(pmod->fstt)) { pprintf(prn, RTFTAB "%s %s\n", tmp, I_("undefined")); } else { pprintf(prn, RTFTAB "%s = %g", tmp, pmod->fstt); print_f_pval_str(f_cdf_comp(pmod->fstt, pmod->dfn, pmod->dfd), prn); } } else if (csv_format(prn)) { pprintf(prn, "\"%s (%d, %d)\"%c", I_("F-statistic"), pmod->dfn, pmod->dfd, prn_delim(prn)); if (na(pmod->fstt)) { pprintf(prn, "\"%s\"\n", I_("undefined")); } else { pprintf(prn, "%.15g%c", pmod->fstt, prn_delim(prn)); print_f_pval_str(f_cdf_comp(pmod->fstt, pmod->dfn, pmod->dfd), prn); } } } static void dwline (const MODEL *pmod, PRN *prn) { if (na(pmod->dw)) { return; } if (plain_format(prn)) { pprintf(prn, " %s = %.*g\n", _("Durbin-Watson statistic"), XDIGITS(pmod), pmod->dw); if (!na(pmod->rho)) { pprintf(prn, " %s = %.*g\n", _("First-order autocorrelation coeff."), XDIGITS(pmod), pmod->rho); } } else if (tex_format(prn)) { char xstr[32]; tex_dcolumn_double(pmod->dw, xstr); pprintf(prn, "%s & %s \\\\\n", I_("Durbin--Watson statistic"), xstr); if (!na(pmod->rho)) { tex_dcolumn_double(pmod->rho, xstr); pprintf(prn, "%s & %s \\\\\n", I_("First-order autocorrelation coeff."), xstr); } } else if (rtf_format(prn)) { pprintf(prn, RTFTAB "%s = %g\n", I_("Durbin-Watson statistic"), pmod->dw); if (!na(pmod->rho)) { pprintf(prn, RTFTAB "%s = %g\n", I_("First-order autocorrelation coeff."), pmod->rho); } } else if (csv_format(prn)) { pprintf(prn, "\"%s\"%c%.15g\n", I_("Durbin-Watson statistic"), prn_delim(prn), pmod->dw); if (!na(pmod->rho)) { pprintf(prn, "\"%s\"%c%.15g\n", I_("First-order autocorrelation coeff."), prn_delim(prn), pmod->rho); } } } static void dhline (const MODEL *pmod, PRN *prn) { double sderr, h = 0.0; int ldepvar = gretl_model_get_int(pmod, "ldepvar"); int T = pmod->nobs - 1; sderr = pmod->sderr[ldepvar - 2]; if (pmod->ess <= 0.0 || (T * sderr * sderr) >= 1.0) return; h = pmod->rho * sqrt(T/(1 - T * sderr * sderr)); if (plain_format(prn)) { char tmp[128]; sprintf(tmp, _("Durbin's h stat. %g"), h); pprintf(prn, " %s\n", tmp); sprintf(tmp, _("(Using variable %d for h stat, with T' = %d)"), pmod->list[ldepvar], T); pprintf(prn, " %s\n", tmp); } else if (rtf_format(prn)) { char tmp[128]; sprintf(tmp, I_("Durbin's h stat. %g"), h); pprintf(prn, RTFTAB "%s\n", tmp); sprintf(tmp, I_("(Using variable %d for h stat, with T' = %d)"), pmod->list[ldepvar], T); pprintf(prn, RTFTAB "%s\n", tmp); } else if (tex_format(prn)) { char x1str[32]; tex_dcolumn_double(h, x1str); pprintf(prn, "%s & %s \\\\\n", I_("Durbin's $h$ statistic"), x1str); } else if (csv_format(prn)) { pprintf(prn, "\"%s\"%c%.15g\n", I_("Durbin's h"), prn_delim(prn), h); } } static int least_signif_coeff (const MODEL *pmod) { double tstat, tmin = 4.0; int i, k = 0; for (i=pmod->ifc; i<pmod->ncoeff; i++) { tstat = fabs(pmod->coeff[i] / pmod->sderr[i]); if (tstat < tmin) { tmin = tstat; k = i; } } if (coeff_pval(pmod->ci, tmin, pmod->dfd) > .10) { return pmod->list[k+2]; } return 0; } static void pval_max_line (const MODEL *pmod, const DATAINFO *pdinfo, PRN *prn) { int k = pmod->ncoeff - pmod->ifc; if (k < 3) return; if ((k = least_signif_coeff(pmod))) { char tmp[128]; if (pmod->ifc) { sprintf(tmp, _("Excluding the constant, p-value was highest " "for variable %d (%s)"), k, pdinfo->varname[k]); } else { sprintf(tmp, _("P-value was highest for variable %d (%s)"), k, pdinfo->varname[k]); } pprintf(prn, "%s\n\n", tmp); } } static const char *aux_string (int aux, PRN *prn) { if (aux == AUX_SQ) { return N_("Auxiliary regression for non-linearity test " "(squared terms)"); } else if (aux == AUX_LOG) { return N_("Auxiliary regression for non-linearity test " "(log terms)"); } else if (aux == AUX_WHITE) { return N_("White's test for heteroskedasticity"); } else if (aux == AUX_CHOW) { return N_("Augmented regression for Chow test"); } else if (aux == AUX_COINT) { if (tex_format(prn)) return N_("Cointegrating regression -- "); else return N_("Cointegrating regression - "); } else if (aux == AUX_ADF) { if (tex_format(prn)) return N_("Augmented Dickey--Fuller regression"); else return N_("Augmented Dickey-Fuller regression"); } else if (aux == AUX_DF) { if (tex_format(prn)) return N_("Dickey--Fuller regression"); else return N_("Dickey-Fuller regression"); } else if (aux == AUX_KPSS) { return N_("KPSS regression"); } else if (aux == AUX_RESET) { return N_("Auxiliary regression for RESET specification test"); } else if (aux == AUX_GROUPWISE) { return N_("Groupwise heteroskedasticity"); } else return ""; } static const char *simple_estimator_string (int ci, PRN *prn) { if (ci == OLS || ci == VAR) return N_("OLS"); else if (ci == WLS) return N_("WLS"); else if (ci == ARCH) return N_("WLS (ARCH)"); else if (ci == TSLS) return N_("TSLS"); else if (ci == HSK) return N_("Heteroskedasticity-corrected"); else if (ci == AR) return N_("AR"); else if (ci == LAD) return N_("LAD"); else if (ci == MPOLS) return N_("High-Precision OLS"); else if (ci == PROBIT) return N_("Probit"); else if (ci == LOGIT) return N_("Logit"); else if (ci == TOBIT) return N_("Tobit"); else if (ci == HECKIT) return N_("Heckit"); else if (ci == POISSON) return N_("Poisson"); else if (ci == NLS) return N_("NLS"); else if (ci == MLE) return N_("ML"); else if (ci == GMM) return N_("GMM"); else if (ci == LOGISTIC) return N_("Logistic"); else if (ci == GARCH) return N_("GARCH"); else if (ci == CORC) { if (tex_format(prn)) return N_("Cochrane--Orcutt"); else return N_("Cochrane-Orcutt"); } else if (ci == HILU) { if (tex_format(prn)) return N_("Hildreth--Lu"); else return N_("Hildreth-Lu"); } else if (ci == PWE) { if (tex_format(prn)) return N_("Prais--Winsten"); else return N_("Prais-Winsten"); } else if (ci == ARBOND) { if (tex_format(prn)) return N_("Arellano--Bond"); else return N_("Arellano-Bond"); } else { return ""; } } const char *estimator_string (const MODEL *pmod, PRN *prn) { if (pmod->ci == ARMA) { if (gretl_model_get_int(pmod, "armax")) { return N_("ARMAX"); } else if (gretl_model_get_int(pmod, "arima_d") || gretl_model_get_int(pmod, "arima_D")) { return N_("ARIMA"); } else { return N_("ARMA"); } } else if (pmod->ci == WLS) { if (gretl_model_get_int(pmod, "iters")) { return N_("Maximum Likelihood"); } else { return N_("WLS"); } } else if (pmod->ci == PANEL) { if (gretl_model_get_int(pmod, "fixed-effects")) { return N_("Fixed-effects"); } else if (gretl_model_get_int(pmod, "random-effects")) { return N_("Random-effects (GLS)"); } else { return N_("Between-groups"); } } else if (pooled_model(pmod)) { return N_("Pooled OLS"); } else if (pmod->ci == ARBOND) { if (gretl_model_get_int(pmod, "step") == 2) { return N_("2-step Arellano-Bond"); } else { return N_("1-step Arellano-Bond"); } } else if (pmod->ci == GMM) { int s = gretl_model_get_int(pmod, "step"); if (s > 2) { return N_("Iterated GMM"); } else if (s == 2) { return N_("2-step GMM"); } else { return N_("1-step GMM"); } } else if (pmod->ci == LOGIT) { if (gretl_model_get_int(pmod, "ordered")) { return N_("Ordered Logit"); } else { return N_("Logit"); } } else if (pmod->ci == PROBIT) { if (gretl_model_get_int(pmod, "ordered")) { return N_("Ordered Probit"); } else { return N_("Probit"); } } else { return simple_estimator_string(pmod->ci, prn); } } static int any_tests (const MODEL *pmod) { if (pmod->ntests > 0) { return 1; } if (pmod->ci == TSLS && gretl_model_get_int(pmod, "stage1-dfn")) { return 1; } return 0; } static void maybe_print_first_stage_F (const MODEL *pmod, PRN *prn) { double F = gretl_model_get_double(pmod, "stage1-F"); int dfn, dfd; if (na(F)) { return; } dfn = gretl_model_get_int(pmod, "stage1-dfn"); dfd = gretl_model_get_int(pmod, "stage1-dfd"); if (dfn <= 0 || dfd <= 0) { return; } if (plain_format(prn)) { pprintf(prn, "%s (%d, %d) = %.*g\n", _("First-stage F-statistic"), dfn, dfd, GRETL_DIGITS, F); pprintf(prn, " %s\n\n", _("A value < 10 may indicate weak instruments")); } else if (tex_format(prn)) { char x1str[32]; tex_dcolumn_double(F, x1str); pprintf(prn, "First-stage $F(%d, %d)$ = %s \\\\\n", dfn, dfd, x1str); } else if (rtf_format(prn)) { pprintf(prn, "%s (%d, %d) = %g\n", I_("First-stage F-statistic"), dfn, dfd, F); } } static void print_model_tests (const MODEL *pmod, PRN *prn) { int i; if (tex_format(prn)) { pputs(prn, "\\vspace{1em}\n\\begin{raggedright}\n"); for (i=0; i<pmod->ntests; i++) { if (i > 0) { pputs(prn, "\\vspace{1ex}\n"); } gretl_model_test_print(pmod, i, prn); } if (pmod->ntests > 0) { pputs(prn, "\\vspace{1ex}\n"); } maybe_print_first_stage_F(pmod, prn); pputs(prn, "\\end{raggedright}\n"); } else { for (i=0; i<pmod->ntests; i++) { gretl_model_test_print(pmod, i, prn); } maybe_print_first_stage_F(pmod, prn); } } static int print_tsls_instruments (const int *list, const DATAINFO *pdinfo, PRN *prn) { int i, j, pos = 0; int ccount = 0; int ninst = 0; char vname[16]; int tex = tex_format(prn); int utf = plain_format(prn); if (utf) { pprintf(prn, "%s: ", _("Instruments")); } else { pprintf(prn, "%s: ", I_("Instruments")); } ccount += strlen(_("Instruments") + 2); for (i=2; i<=list[0]; i++) { if (list[i] == LISTSEP) { pos = i; continue; } if (pos && list[i] > 0) { int dup = 0; for (j=2; j<pos; j++) { if (list[i] == list[j]) { dup = 1; break; } } if (!dup) { if (tex) { tex_escape(vname, pdinfo->varname[list[i]]); } else { strcpy(vname, pdinfo->varname[list[i]]); } pprintf(prn, "%s ", vname); ccount += strlen(vname) + 1; if (ccount >= 64) { if (tex) { pputs(prn, "\\\\\n"); } else if (rtf_format(prn)) { pputs(prn, "\\par\n"); } else { pputs(prn, "\n "); } ccount = 0; } ninst++; } } } if (ninst == 0) { pputs(prn, _("none")); } if (ccount > 0) { if (tex) { pputs(prn, "\\\\\n"); } else if (rtf_format(prn)) { pputs(prn, "\\par\n"); } else { pputs(prn, "\n"); } } return 0; } static void arbond_asy_vcv_line (const MODEL *pmod, PRN *prn) { if (csv_format(prn)) { pprintf(prn, "\"%s\"", I_("Asymptotic standard errors (unreliable)")); } else if (plain_format(prn)) { pputs(prn, _("Asymptotic standard errors (unreliable)")); } else { pputs(prn, I_("Asymptotic standard errors (unreliable)")); } pputc(prn, '\n'); } static void panel_robust_vcv_line (PRN *prn) { if (csv_format(prn)) { pprintf(prn, "\"%s\"", I_("Robust (HAC) standard errors")); } else if (plain_format(prn)) { pputs(prn, _("Robust (HAC) standard errors")); } else { pputs(prn, I_("Robust (HAC) standard errors")); } pputc(prn, '\n'); } static void beck_katz_vcv_line (PRN *prn) { if (csv_format(prn)) { pprintf(prn, "\"%s\"", I_("Beck-Katz standard errors")); } else if (plain_format(prn)) { pputs(prn, _("Beck-Katz standard errors")); } else if (tex_format(prn)) { pputs(prn, I_("Beck--Katz standard errors")); } else { pputs(prn, I_("Beck-Katz standard errors")); } pputc(prn, '\n'); } static void beck_katz_failed_line (PRN *prn) { if (plain_format(prn)) { pputs(prn, _("Could not compute Beck-Katz standard errors")); pputc(prn, '\n'); } } static void hac_vcv_line (const MODEL *pmod, PRN *prn) { const char *kstrs[] = { N_("Bartlett kernel"), N_("Parzen kernel"), N_("QS kernel") }; int kern = gretl_model_get_int(pmod, "hac_kernel"); int h = gretl_model_get_int(pmod, "hac_lag"); int white = gretl_model_get_int(pmod, "hac_prewhiten"); double bt; if (kern == KERNEL_QS) { bt = gretl_model_get_double(pmod, "qs_bandwidth"); if (plain_format(prn)) { pprintf(prn, _("HAC standard errors, " "bandwidth %.2f"), bt); } else { pprintf(prn, I_("HAC standard errors, " "bandwidth %.2f"), bt); } } else { if (plain_format(prn)) { pprintf(prn, _("HAC standard errors, " "bandwidth %d"), h); } else { pprintf(prn, I_("HAC standard errors, " "bandwidth %d"), h); } } pputc(prn, ' '); if (plain_format(prn)) { pprintf(prn, "(%s", _(kstrs[kern - 1])); } else { pprintf(prn, "(%s", I_(kstrs[kern - 1])); } if (white) { pputs(prn, ", "); pputs(prn, (plain_format(prn))? _("prewhitened") : I_("prewhitened")); } pputs(prn, ")\n"); } static void hc_vcv_line (const MODEL *pmod, PRN *prn) { int hcv = gretl_model_get_int(pmod, "hc_version"); int jack = 0; if (hcv == 4) { jack = 1; hcv--; } if (plain_format(prn)) { pprintf(prn, "%s, %s%sHC%d%s", _("Heteroskedasticity-robust standard errors"), (jack)? "" : _("variant"), (jack)? "" : " ", hcv, (jack)? " (jackknife)" : ""); } else { pprintf(prn, "%s, %s%sHC%d%s", I_("Heteroskedasticity-robust standard errors"), (jack)? "" : I_("variant"), (jack)? "" : " ", hcv, (jack)? " (jackknife)" : ""); } if (rtf_format(prn)) { pputs(prn, "\\par\n"); } else { pputc(prn, '\n'); } } static void ml_vcv_line (const MODEL *pmod, PRN *prn) { int v = gretl_model_get_int(pmod, "ml_vcv"); int tex = tex_format(prn); int utf = plain_format(prn); const char *vcvstr = NULL; switch (v) { case VCV_HESSIAN: vcvstr = N_("Standard errors based on Hessian"); break; case VCV_IM: vcvstr = N_("Standard errors based on Information Matrix"); break; case VCV_OP: vcvstr = N_("Standard errors based on Outer Products matrix"); break; case VCV_QML: vcvstr = N_("QML standard errors"); break; case VCV_BW: if (tex) { vcvstr = N_("Bollerslev--Wooldridge standard errors"); } else { vcvstr = N_("Bollerslev-Wooldridge standard errors"); } break; default: break; } if (vcvstr != NULL) { if (csv_format(prn)) { pprintf(prn, "\"%s\"\n", I_(vcvstr)); } else { pprintf(prn, "%s\n", (utf)? _(vcvstr) : I_(vcvstr)); } } } static void tex_vecm_depvar_name (char *s, const char *vname) { char tmp[14]; int gotit = 0; if (sscanf(vname, "d_%13s", tmp)) { char myvar[24]; tex_escape(myvar, tmp); sprintf(s, "$\\Delta$%s", myvar); gotit = 1; } if (!gotit) { tex_escape(s, vname); } } static void tex_arbond_depvar_name (char *s, const char *vname) { char vnesc[32]; tex_escape(vnesc, vname); sprintf(s, "$\\Delta$%s", vnesc); } void print_model_vcv_info (const MODEL *pmod, PRN *prn) { if (gretl_model_get_int(pmod, "hac_kernel")) { hac_vcv_line(pmod, prn); } else if (gretl_model_get_int(pmod, "hc")) { hc_vcv_line(pmod, prn); } else if (gretl_model_get_int(pmod, "ml_vcv")) { ml_vcv_line(pmod, prn); } else if (gretl_model_get_int(pmod, "panel_hac")) { panel_robust_vcv_line(prn); } else if (gretl_model_get_int(pmod, "panel_bk")) { beck_katz_vcv_line(prn); } else if (gretl_model_get_int(pmod, "panel_bk_failed")) { beck_katz_failed_line(prn); } else if (pmod->ci == ARBOND && gretl_model_get_int(pmod, "asy")) { arbond_asy_vcv_line(pmod, prn); } } static void print_extra_list (const char *tag, const int *list, const DATAINFO *pdinfo, PRN *prn) { int i, v, len; len = pputs(prn, _(tag)); for (i=1; i<=list[0]; i++) { v = list[i]; if (v < pdinfo->v) { len += pprintf(prn, " %s", pdinfo->varname[v]); } else { len += pprintf(prn, " %d", v); } if (len > 68 && i < list[0]) { pputc(prn, '\n'); len = 0; } } pputc(prn, '\n'); } static void print_model_zerolist (const MODEL *pmod, const DATAINFO *pdinfo, PRN *prn) { const int *zlist = gretl_model_get_data(pmod, "zerolist"); const char *tag = N_("Omitted because all values were zero:"); if (pmod->ci == PANEL && gretl_model_get_int(pmod, "between")) { return; } print_extra_list(tag, zlist, pdinfo, prn); } static void print_model_droplist (const MODEL *pmod, const DATAINFO *pdinfo, PRN *prn) { const int *dlist = gretl_model_get_data(pmod, "droplist"); const char *tag = N_("Omitted due to exact collinearity:"); if (pmod->ci == PANEL && gretl_model_get_int(pmod, "between")) { return; } print_extra_list(tag, dlist, pdinfo, prn); } static void print_tsls_droplist (const MODEL *pmod, const DATAINFO *pdinfo, PRN *prn) { const int *dlist = gretl_model_get_data(pmod, "inst_droplist"); int i, v; pputs(prn, _("Redundant instruments:")); for (i=1; i<=dlist[0]; i++) { v = dlist[i]; if (v < pdinfo->v) { pprintf(prn, " %s", pdinfo->varname[v]); } else { pprintf(prn, " %d", v); } } pputc(prn, '\n'); } static void print_arma_depvar (const MODEL *pmod, const DATAINFO *pdinfo, PRN *prn) { int tex = tex_format(prn); int utf = plain_format(prn); int yno = gretl_model_get_depvar(pmod); int d = gretl_model_get_int(pmod, "arima_d"); int D = gretl_model_get_int(pmod, "arima_D"); char vname[64]; *vname = 0; if (tex) { char tmp[32]; if (d > 0 || D > 0) { strcat(vname, "$"); } if (d == 1) { strcat(vname, "(1-L)"); } else if (d == 2) { strcat(vname, "(1-L)^2"); } if (D == 1) { strcat(vname, "(1-L^s)"); } else if (D == 2) { strcat(vname, "(1-L^s)^2"); } if (d > 0 || D > 0) { strcat(vname, "$"); } tex_escape(tmp, pdinfo->varname[yno]); strcat(vname, tmp); } else { if (d == 1) { strcat(vname, "(1-L)"); } else if (d == 2) { strcat(vname, "(1-L)^2"); } if (D == 1) { strcat(vname, "(1-Ls)"); } else if (D == 2) { strcat(vname, "(1-Ls)^2"); } if (d > 0 || D > 0) { strcat(vname, " "); } strcat(vname, pdinfo->varname[yno]); } pprintf(prn, "%s: %s", (utf)? _("Dependent variable") : I_("Dependent variable"), vname); } static void arma_extra_info (const MODEL *pmod, PRN *prn) { int acode = gretl_model_get_int(pmod, "arma_flags"); if (acode & ARMA_X12A) { pputs(prn, _("Estimated using X-12-ARIMA")); pputs(prn, " ("); pputs(prn, (acode & ARMA_EXACT)? _("exact ML") : _("conditional ML")); pputs(prn, ")\n"); } else if (acode & ARMA_EXACT) { pputs(prn, _("Estimated using Kalman filter")); pputs(prn, " ("); pputs(prn, _("exact ML")); pputs(prn, ")\n"); } else { pputs(prn, _("Estimated using BHHH method")); pputs(prn, " ("); pputs(prn, _("conditional ML")); pputs(prn, ")\n"); } } static void print_model_heading (const MODEL *pmod, const DATAINFO *pdinfo, gretlopt opt, PRN *prn) { char startdate[OBSLEN], enddate[OBSLEN], vname[32]; int t1 = pmod->t1, t2 = pmod->t2; int tex = tex_format(prn); int utf = plain_format(prn); int csv = csv_format(prn); int dvnl = 1; int order = 0; if (pmod->aux != AUX_VAR && pmod->aux != AUX_VECM) { ntodate(startdate, t1, pdinfo); ntodate(enddate, t2, pdinfo); } switch (pmod->aux) { case AUX_SQ: case AUX_LOG: case AUX_WHITE: case AUX_CHOW: case AUX_COINT: case AUX_ADF: case AUX_DF: case AUX_KPSS: case AUX_RESET: case AUX_GROUPWISE: if (utf) { pprintf(prn, "\n%s\n", _(aux_string(pmod->aux, prn))); } else if (tex) { pprintf(prn, "\n%s\n", I_(aux_string(pmod->aux, prn))); } else if (csv) { pprintf(prn, "\"%s\"\n", I_(aux_string(pmod->aux, prn))); } else { /* RTF */ pprintf(prn, "%s\\par\n", I_(aux_string(pmod->aux, prn))); } break; case AUX_AR: order = gretl_model_get_int(pmod, "BG_order"); if (utf) { pprintf(prn, "\n%s ", _("Breusch-Godfrey test for")); } else { pprintf(prn, "\n%s ", I_("Breusch-Godfrey test for")); } if (order > 1) { pprintf(prn, "%s %d\n", (utf)? _("autocorrelation up to order") : I_("autocorrelation up to order"), order); } else { pprintf(prn, "%s\n", (utf)? _("first-order autocorrelation") : I_("first-order autocorrelation")); } break; case AUX_ARCH: order = gretl_model_get_int(pmod, "arch_order"); pprintf(prn, "\n%s %d\n", (utf)? _("Test for ARCH of order") : I_("Test for ARCH of order"), order); break; case AUX_SYS: pprintf(prn, "%s %d: ", (utf)? _("Equation") : I_("Equation"), pmod->ID + 1); break; case AUX_VAR: pprintf(prn, "\n%s %d: ", (utf)? _("Equation") : I_("Equation"), pmod->ID); break; case AUX_VECM: pprintf(prn, "%s %d: ", (utf)? _("Equation") : I_("Equation"), pmod->ID); break; case AUX_AUX: pputc(prn, '\n'); break; case AUX_ADD: default: if (pmod->ID < 0 || (opt & OPT_S)) { if (!csv) { pputc(prn, '\n'); } } else if (pmod->name) { if (csv) { pprintf(prn, "\"%s:\"\n", pmod->name); } else { pprintf(prn, "\n%s:\n", pmod->name); } } else { if (csv) { pprintf(prn, "\"%s %d: ", I_("Model"), pmod->ID); } else { pprintf(prn, "\n%s %d: ", (utf)? _("Model") : I_("Model"), pmod->ID); } } break; } if (pmod->aux == AUX_VAR || pmod->aux == AUX_VECM) { ; } else if (pmod->aux == AUX_SYS) { pprintf(prn, (utf)? _("%s estimates using the %d observations %s%s%s") : I_("%s estimates using the %d observations %s%s%s"), _(gretl_system_short_string(pmod)), pmod->nobs, startdate, (tex)? "--" : "-", enddate); } else if (!dataset_is_panel(pdinfo)) { if (pmod->missmask != NULL) { int mc = model_missval_count(pmod); if (pmod->ci == HECKIT) { int Tmax = pmod->t2 - pmod->t1 + 1; mc = Tmax - gretl_model_get_int(pmod, "totobs"); } pprintf(prn, (utf)? _("%s estimates using %d observations from %s%s%s") : I_("%s estimates using %d observations from %s%s%s"), _(estimator_string(pmod, prn)), pmod->nobs, startdate, (tex)? "--" : "-", enddate); if (mc > 0) { gretl_prn_newline(prn); pprintf(prn, "%s: %d", (utf)? _("Missing or incomplete observations dropped") : I_("Missing or incomplete observations dropped"), mc); } } else { pprintf(prn, (utf)? _("%s estimates using the %d observations %s%s%s") : I_("%s estimates using the %d observations %s%s%s"), _(estimator_string(pmod, prn)), pmod->nobs, startdate, (tex)? "--" : "-", enddate); } } else { int effn = gretl_model_get_int(pmod, "n_included_units"); int Tmin = gretl_model_get_int(pmod, "Tmin"); int Tmax = gretl_model_get_int(pmod, "Tmax"); pprintf(prn, (utf)? _("%s estimates using %d observations") : I_("%s estimates using %d observations"), _(estimator_string(pmod, prn)), pmod->nobs); if (effn > 0) { gretl_prn_newline(prn); pprintf(prn, (utf)? _("Included %d cross-sectional units") : I_("Included %d cross-sectional units"), effn); } if (Tmin > 0 && Tmax > 0) { gretl_prn_newline(prn); if (Tmin == Tmax) { pprintf(prn, (utf)? _("Time-series length = %d") : I_("Time-series length = %d"), Tmin); } else { pprintf(prn, (utf)? _("Time-series length: minimum %d, maximum %d") : I_("Time-series length: minimum %d, maximum %d"), Tmin, Tmax); } } } if (csv) pputc(prn, '"'); if (pmod->aux != AUX_VAR && pmod->aux != AUX_VECM) { gretl_prn_newline(prn); } if (pmod->ci == ARMA && plain_format(prn)) { arma_extra_info(pmod, prn); } if (csv) pputc(prn, '"'); /* special formulations for dependent variable in various cases */ if (pmod->aux == AUX_SQ || pmod->aux == AUX_LOG) { pprintf(prn, "%s: %s", (utf)? _("Dependent variable") : I_("Dependent variable"), (tex)? "$\\hat{u}$" : "uhat"); } else if (pmod->aux == AUX_WHITE) { pprintf(prn, "%s: %s", (utf)? _("Dependent variable") : I_("Dependent variable"), (tex)? "$\\hat{u}^2$" : "uhat^2"); } else if (pmod->aux == AUX_ARCH) { pprintf(prn, "%s: %s", (utf)? _("Dependent variable") : I_("Dependent variable"), (tex)? "$u_t^2$" : "ut^2"); } else if (pmod->ci == NLS) { if (tex) tex_escape(vname, pmod->depvar); pprintf(prn, "%s: %s", (utf)? _("Dependent variable") : I_("Dependent variable"), (tex)? vname : pmod->depvar); } else if (pmod->ci == MLE || pmod->ci == GMM) { if (pmod->depvar != NULL) { if (tex) { pprintf(prn, "\\verb!%s!", pmod->depvar); } else { pputs(prn, pmod->depvar); } } else { dvnl = 0; } } else if (pmod->ci == ARMA) { print_arma_depvar(pmod, pdinfo, prn); } else { int v = gretl_model_get_depvar(pmod); if (tex) { if (pmod->aux == AUX_VECM) { tex_vecm_depvar_name(vname, pdinfo->varname[v]); } else if (pmod->ci == ARBOND) { tex_arbond_depvar_name(vname, pdinfo->varname[v]); } else { tex_escape(vname, pdinfo->varname[v]); } } if (pmod->aux == AUX_VAR || pmod->aux == AUX_VECM) { pputs(prn, (tex)? vname : pdinfo->varname[v]); } else { pprintf(prn, "%s: %s", (utf)? _("Dependent variable") : I_("Dependent variable"), (tex)? vname : pdinfo->varname[v]); } } if (csv) pputc(prn, '"'); if (dvnl) { gretl_prn_newline(prn); } /* supplementary strings below the estimator and sample info */ /* list of instruments for TSLS */ if (pmod->ci == TSLS) { int method = gretl_model_get_int(pmod, "method"); if (method != SYS_FIML && method != SYS_LIML) { print_tsls_instruments(pmod->list, pdinfo, prn); } } /* VCV variants */ print_model_vcv_info(pmod, prn); /* WLS on panel data */ if (gretl_model_get_int(pmod, "unit_weights") && !pmod->aux) { if (tex) { pputs(prn, "\\\\\n"); } if (gretl_model_get_int(pmod, "iters")) { pprintf(prn, (utf)? _("Allowing for groupwise heteroskedasticity") : I_("Allowing for groupwise heteroskedasticity")); } else { pprintf(prn, (utf)? _("Weights based on per-unit error variances") : I_("Weights based on per-unit error variances")); } pputc(prn, '\n'); } /* weight variable for WLS */ else if ((pmod->ci == WLS && !pmod->aux)) { if (tex) { tex_escape(vname, pdinfo->varname[pmod->nwt]); } if (csv) pputc(prn, '"'); pprintf(prn, "%s: %s", (utf)? _("Variable used as weight") : I_("Variable used as weight"), (tex)? vname : pdinfo->varname[pmod->nwt]); if (csv) pputc(prn, '"'); pputc(prn, '\n'); } /* weight variable for ARCH */ else if (pmod->ci == ARCH) { if (csv) pputc(prn, '"'); pprintf(prn, "%s: %s", (utf)? _("Variable used as weight") : I_("Variable used as weight"), (tex)? "$1/\\hat{\\sigma}_t$" : "1/sigma"); if (csv) pputc(prn, '"'); pputc(prn, '\n'); } /* rhohat for CORC and HILU (TeX) */ else if (pmod->ci == CORC || pmod->ci == HILU || pmod->ci == PWE) { if (tex) { pprintf(prn, "$\\hat{\\rho}$ = %g\n", gretl_model_get_double(pmod, "rho_in")); } } /* y-hat formula for logistic regression */ else if (pmod->ci == LOGISTIC) { if (tex) { pprintf(prn, "$\\hat{y} = %g / (1 + e^{-X\\hat{\\beta}})$\n", gretl_model_get_double(pmod, "lmax")); } else { pprintf(prn, "yhat = %g / (1 + exp(-X*b))\n", gretl_model_get_double(pmod, "lmax")); } } /* TSLS: message about redundant instruments */ if (plain_format(prn) && pmod->ci == TSLS && gretl_model_get_data(pmod, "inst_droplist") != NULL) { print_tsls_droplist(pmod, pdinfo, prn); } /* messages about collinear and/or zero regressors */ if (plain_format(prn)) { if (gretl_model_get_data(pmod, "zerolist") != NULL) { print_model_zerolist(pmod, pdinfo, prn); } if (gretl_model_get_data(pmod, "droplist") != NULL) { print_model_droplist(pmod, pdinfo, prn); } } if (pmod->missmask == NULL && gretl_model_get_int(pmod, "wt_dummy")) { /* FIXME alt formats */ pprintf(prn, "%s %d\n", (utf)? _("Weight var is a dummy variable, effective obs =") : I_("Weight var is a dummy variable, effective obs ="), pmod->nobs); } if (rtf_format(prn)) { pputs(prn, "\\par\n"); } else { pputc(prn, '\n'); } } static void model_format_start (PRN *prn) { if (tex_format(prn)) { if (tex_doc_format(prn)) { gretl_tex_preamble(prn, 0); } else { pputs(prn, "%% You'll need to \\usepackage{dcolumn}\n\n"); } pputs(prn, "\\begin{center}\n"); } else if (rtf_format(prn)) { if (rtf_doc_format(prn)) { pputs(prn, "{\\rtf1\\par\n\\qc "); } else { pputs(prn, "\\par\n\\qc "); } } } #define RTF_COEFF_ROW "\\trowd \\trqc \\trgaph30\\trleft-30\\trrh262" \ "\\cellx1900\\cellx3300\\cellx4700\\cellx6100" \ "\\cellx7500\\cellx8000\n\\intbl" #define RTF_BINARY_ROW "\\trowd \\trqc \\trgaph30\\trleft-30\\trrh262" \ "\\cellx1900\\cellx3300\\cellx4700\\cellx6100" \ "\\cellx8000\n\\intbl" #define RTF_ROOT_ROW "\\trowd \\trqc \\trgaph30\\trleft-30\\trrh262" \ "\\cellx500\\cellx1500\\cellx2900\\cellx4300" \ "\\cellx5700\\cellx7100\n\\intbl" void print_coeff_heading (int mode, PRN *prn) { if (mode == COEFF_HEADING_VARNAME) { pputs(prn, _(" VARIABLE COEFFICIENT STDERROR" " T STAT P-VALUE\n\n")); } else { pputs(prn, _(" PARAMETER ESTIMATE STDERROR" " T STAT P-VALUE\n\n")); } } static void print_coeff_table_start (const MODEL *pmod, PRN *prn) { int slopes = binary_model(pmod) && !gretl_model_get_int(pmod, "show-pvals"); int use_param = pmod->ci == NLS || pmod->ci == MLE || pmod->ci == GMM; if (plain_format(prn)) { if (pmod->ci == MPOLS) { pputs(prn, _(" VARIABLE COEFFICIENT " " STDERROR\n")); pputc(prn, '\n'); } else if (slopes) { pputs(prn, _(" VARIABLE COEFFICIENT STDERROR" " T STAT SLOPE\n")); pprintf(prn, " " " %s\n", _("(at mean)")); } else { print_coeff_heading(use_param, prn); } return; } else if (csv_format(prn)) { char d = prn_delim(prn); if (pmod->ci == MPOLS) { pprintf(prn, "\"%s\"%c\"%s\"%c\"%s\"\n", I_("VARIABLE"), d, I_("COEFFICIENT"), d, I_("STDERROR")); } else if (slopes) { pprintf(prn, "\"%s\"%c\"%s\"%c\"%s\"%c\"%s\"%c\"%s\"\n", I_("VARIABLE"), d, I_("COEFFICIENT"), d, I_("STDERROR"), d, I_("T STAT"), d, I_("SLOPE at mean")); } else if (use_param) { pprintf(prn, "\"%s\"%c\"%s\"%c\"%s\"%c\"%s\"%c\"%s\"\n", I_("PARAMETER"), d, I_("ESTIMATE"), d, I_("STDERROR"), d, I_("T STAT"), d, I_("P-VALUE")); } else { pprintf(prn, "\"%s\"%c\"%s\"%c\"%s\"%c\"%s\"%c\"%s\"\n", I_("VARIABLE"), d, I_("COEFFICIENT"), d, I_("STDERROR"), d, I_("T STAT"), d, I_("P-VALUE")); } } else { char col1[16], col2[16]; if (use_param) { strcpy(col1, N_("Parameter")); strcpy(col2, N_("Estimate")); } else { strcpy(col1, N_("Variable")); strcpy(col2, N_("Coefficient")); } if (tex_format(prn)) { tex_coeff_table_start(col1, col2, slopes, prn); return; } if (rtf_format(prn)) { if (slopes) { pprintf(prn, "{" RTF_BINARY_ROW " \\qc {\\i %s}\\cell" " \\qc {\\i %s}\\cell" " \\qc {\\i %s}\\cell" " \\qc {\\i %s}\\cell" " \\qc {\\i %s{\\super *}}\\cell" " \\intbl \\row\n", I_(col1), I_(col2), I_("Std. Error"), I_("t-statistic"), I_("Slope")); } else { pprintf(prn, "{" RTF_COEFF_ROW " \\qc {\\i %s}\\cell" " \\qc {\\i %s}\\cell" " \\qc {\\i %s}\\cell" " \\qc {\\i %s}\\cell" " \\qc {\\i %s}\\cell" " \\ql \\cell" " \\intbl \\row\n", I_(col1), I_(col2), I_("Std. Error"), I_("t-statistic"), I_("p-value")); } return; } } } static char pvalue_level(const double pval) { static char pflag=0; /* First time inicialization */ if(pval==-1) { pflag=0; return(pflag); } /* Stored value query */ if(pval==-2) return(pflag); if(pval<0.01) { pflag|=1; }else if(pval<0.05) { pflag|=2; }else if(pval<0.1) { pflag|=4; } return(pflag); } static void print_coeff_table_end (const MODEL *pmod, PRN *prn) { if (plain_format(prn) || csv_format(prn)) { pputc(prn, '\n'); /* check if there are p-values for 1, 5 or 10 percent level of acceptance */ char pval_lvl; pval_lvl=pvalue_level(-2); if(pval_lvl&4) pprintf(prn, " %s\n", _("* indicates significance at the 10 percent level")); if(pval_lvl&2) pprintf(prn, " %s\n", _("** indicates significance at the 5 percent level")); if(pval_lvl&1) pprintf(prn, " %s\n", _("*** indicates significance at the 1 percent level")); if(pval_lvl>0) pputc(prn, '\n'); /* FIXME Must adapt to other output formats. New POT string for *** level */ } else if (tex_format(prn)) { tex_coeff_table_end(prn); } else if (rtf_format(prn)) { pputs(prn, "}\n\n"); } if (plain_format(prn) && gretl_model_get_int(pmod, "near-singular")) { const char *msg = N_("Warning: data matrix close to singularity!"); pprintf(prn, "%s\n\n", _(msg)); } } static void model_format_end (PRN *prn) { if (tex_format(prn)) { pputs(prn, "\n\\end{center}\n"); if (tex_doc_format(prn)) { pputs(prn, "\n\\end{document}\n"); } } else if (rtf_doc_format(prn)) { pputs(prn, "\n}\n"); } } static void print_middle_table_start (PRN *prn) { if (tex_format(prn)) { char pt = get_local_decpoint(); pprintf(prn, "\\vspace{1em}\n\n" "\\begin{tabular}{lD{%c}{%c}{-1}}\n", pt, pt); } } static void print_middle_table_end (PRN *prn) { if (tex_format(prn)) { pputs(prn, "\\end{tabular}\n\n"); } else if (rtf_format(prn)) { pputs(prn, "\\par\n"); } else { pputc(prn, '\n'); } } static void r_squared_message (const MODEL *pmod, PRN *prn) { if (na(pmod->rsq)) { return; } pprintf(prn, "%s.\n\n", _("R-squared is computed as the square of the correlation " "between observed and\nfitted values of the dependent variable")); } static void weighted_stats_message (PRN *prn) { const char *msg = N_("Statistics based on the weighted data"); if (plain_format(prn)) { pprintf(prn, "%s:\n\n", _(msg)); } else if (tex_format(prn)) { pprintf(prn, "\\vspace{1em}%s:\n\n", I_(msg)); } else { /* RTF */ pprintf(prn, "\\par \\qc\n%s:\n\n", I_(msg)); } } static void original_stats_message (PRN *prn) { const char *msg = N_("Statistics based on the original data"); if (plain_format(prn)) { pprintf(prn, "%s:\n\n", _(msg)); } else if (tex_format(prn)) { pprintf(prn, "\\vspace{1em}\n%s:\n\n", I_(msg)); } else { /* RTF */ pprintf(prn, "\\par \\qc\n%s:\n\n", I_(msg)); } } static void rho_differenced_stats_message (PRN *prn) { const char *msg = N_("Statistics based on the rho-differenced data"); if (plain_format(prn)) { pprintf(prn, "%s:\n\n", _(msg)); } else if (tex_format(prn)) { pprintf(prn, "\\vspace{1em}\n%s:\n\n", I_(msg)); } else { /* RTF */ pprintf(prn, "\\par \\qc\n%s:\n\n", I_(msg)); } } static void print_whites_results (const MODEL *pmod, PRN *prn) { if (plain_format(prn)) { pprintf(prn, "\n%s: TR^2 = %f,\n", _("Test statistic"), pmod->rsq * pmod->nobs); pprintf(prn, "%s = P(%s(%d) > %f) = %f\n\n", _("with p-value"), _("Chi-square"), pmod->ncoeff - 1, pmod->rsq * pmod->nobs, chisq_cdf_comp(pmod->rsq * pmod->nobs, pmod->ncoeff - 1)); } else if (rtf_format(prn)) { /* FIXME */ pprintf(prn, "\\par \\ql\n%s: TR{\\super 2} = %f,\n", I_("Test statistic"), pmod->rsq * pmod->nobs); pprintf(prn, "%s = P(%s(%d) > %f) = %f\n\n", I_("with p-value"), I_("Chi-square"), pmod->ncoeff - 1, pmod->rsq * pmod->nobs, chisq_cdf_comp(pmod->rsq * pmod->nobs, pmod->ncoeff - 1)); } else if (tex_format(prn)) { pprintf(prn, "\n%s: $TR^2$ = %f,\n", I_("Test statistic"), pmod->rsq * pmod->nobs); pprintf(prn, "%s = $P$($\\chi^2(%d)$ > %f) = %f\n\n", I_("with p-value"), pmod->ncoeff - 1, pmod->rsq * pmod->nobs, chisq_cdf_comp(pmod->rsq * pmod->nobs, pmod->ncoeff - 1)); } } static void print_ll (const MODEL *pmod, PRN *prn) { int lldig; if (na(pmod->lnL)) { return; } if (pmod->ci == ARMA) { lldig = 8; } else { lldig = XDIGITS(pmod); } if (plain_format(prn)) { double jll; pprintf(prn, " %s = %.*g\n", _("Log-likelihood"), lldig, pmod->lnL); jll = gretl_model_get_double(pmod, "jll"); if (!na(jll)) { char jllstr[64]; sprintf(jllstr, _("Log-likelihood for %s"), (const char *) gretl_model_get_data(pmod, "log-parent")); pprintf(prn, " (%s = %.*g)\n", jllstr, lldig, jll); } } else if (rtf_format(prn)) { pprintf(prn, RTFTAB "%s = %.*g\n", I_("Log-likelihood"), GRETL_DIGITS, pmod->lnL); } else if (tex_format(prn)) { char xstr[32]; tex_dcolumn_double(pmod->lnL, xstr); pprintf(prn, "%s & %s \\\\\n", I_("Log-likelihood"), xstr); } } static char active_decpoint (void) { char test[4]; sprintf(test, "%.1f", 1.0); return test[1]; } #define fixed_effects_model(m) (m->ci == PANEL && \ gretl_model_get_int(m, "fixed-effects")) #define random_effects_model(m) (m->ci == PANEL && \ gretl_model_get_int(m, "random-effects")) #define between_model(m) (m->ci == PANEL && \ gretl_model_get_int(m, "between")) /** * printmodel: * @pmod: pointer to gretl model. * @pdinfo: data information struct. * @opt: may contain %OPT_O to print covariance matrix, %OPT_S * to get a "simple" print (just coefficients and standard * errors). * @prn: gretl printing struct. * * Print to @prn the estimates in @pmod plus associated statistics. * * Returns: 0 on success, 1 if some of the values to print were %NaN. */ int printmodel (MODEL *pmod, const DATAINFO *pdinfo, gretlopt opt, PRN *prn) { int binary = binary_model(pmod); int gotnan = 0; if (prn == NULL || (opt & OPT_Q)) { return 0; } if (csv_format(prn)) { if (active_decpoint() == ',') { gretl_print_set_delim(prn, '\t'); } else { gretl_print_set_delim(prn, ','); } } if (!plain_format(prn)) { model_format_start(prn); } else if (pmod->ci != NLS) { int iters = gretl_model_get_int(pmod, "iters"); if (iters > 0) { pprintf(prn, _("Convergence achieved after %d iterations\n"), iters); } else { int fncount = gretl_model_get_int(pmod, "fncount"); int grcount = gretl_model_get_int(pmod, "grcount"); if (fncount > 0) { pprintf(prn, _("Function evaluations: %d\n"), fncount); pprintf(prn, _("Evaluations of gradient: %d\n"), grcount); } } } print_model_heading(pmod, pdinfo, opt, prn); print_coeff_table_start(pmod, prn); gotnan = print_coefficients(pmod, pdinfo, prn); if (pmod->ci == AR) { print_rho_terms(pmod, prn); } else if (pmod->ci == POISSON) { print_poisson_offset(pmod, pdinfo, prn); } /* This is the place to have the pvalues * legends */ print_coeff_table_end(pmod, prn); if (pmod->aux == AUX_ARCH || pmod->aux == AUX_ADF || pmod->aux == AUX_RESET || pmod->aux == AUX_DF || pmod->aux == AUX_KPSS) { goto close_format; } if (binary) { print_binary_statistics(pmod, pdinfo, prn); goto close_format; } if (pmod->ci == POISSON) { print_middle_table_start(prn); depvarstats(pmod, prn); pseudorsqline(pmod, prn); print_ll(pmod, prn); info_stats_lines(pmod, prn); print_middle_table_end(prn); goto close_format; } if (pmod->ci == TOBIT) { print_middle_table_start(prn); depvarstats(pmod, prn); print_tobit_stats(pmod, prn); print_ll(pmod, prn); info_stats_lines(pmod, prn); print_middle_table_end(prn); goto close_format; } if (ordered_model(pmod)) { print_middle_table_start(prn); print_ll(pmod, prn); info_stats_lines(pmod, prn); print_middle_table_end(prn); goto close_format; } if (pmod->ci == LAD) { print_middle_table_start(prn); depvarstats(pmod, prn); ladstats(pmod, prn); print_middle_table_end(prn); goto close_format; } if (pmod->ci == GARCH) { print_middle_table_start(prn); depvarstats(pmod, prn); garch_variance_line(pmod, prn); print_ll(pmod, prn); info_stats_lines(pmod, prn); print_middle_table_end(prn); goto close_format; } if (pmod->ci == ARBOND || pmod->ci == GMM) { print_middle_table_start(prn); essline(pmod, prn); print_GMM_test_data(pmod, prn); print_middle_table_end(prn); goto close_format; } if (pmod->ci == HECKIT) { print_middle_table_start(prn); depvarstats(pmod, prn); print_heckit_stats(pmod, prn); print_middle_table_end(prn); goto close_format; } if (pmod->aux == AUX_SYS) { print_middle_table_start(prn); depvarstats(pmod, prn); essline(pmod, prn); if (gretl_model_get_int(pmod, "method") == SYS_LIML) { print_liml_equation_data(pmod, prn); } print_middle_table_end(prn); goto close_format; } if (pmod->aux == AUX_SQ || pmod->aux == AUX_LOG || pmod->aux == AUX_AR) { print_middle_table_start(prn); rsqline(pmod, prn); print_middle_table_end(prn); goto close_format; } if (pmod->aux == AUX_COINT) { rsqline(pmod, prn); dwline(pmod, prn); info_stats_lines(pmod, prn); if (!plain_format(prn)) { print_middle_table_end(prn); } goto close_format; } if (opt & OPT_S) { /* --simple-print */ goto close_format; } if (pmod->aux == AUX_WHITE) { rsqline(pmod, prn); print_whites_results(pmod, prn); goto close_format; } if (pmod->ci == ARMA) { print_middle_table_start(prn); depvarstats(pmod, prn); print_arma_stats(pmod, prn); print_ll(pmod, prn); info_stats_lines(pmod, prn); print_middle_table_end(prn); print_arma_roots(pmod, prn); goto close_format; } if (pmod->ci == LOGISTIC) { original_stats_message(prn); } if (pmod->ci == OLS || pmod->ci == VAR || pmod->ci == TSLS || pmod->ci == NLS || pmod->ci == MPOLS || (pmod->ci == AR && pmod->arinfo->arlist[0] == 1) || pmod->ci == LOGISTIC || pmod->ci == TOBIT || pmod->ci == PANEL || (pmod->ci == WLS && gretl_model_get_int(pmod, "wt_dummy"))) { print_middle_table_start(prn); if (pmod->ci != VAR) { depvarstats(pmod, prn); } if (essline(pmod, prn)) { print_middle_table_end(prn); goto close_format; } rsqline(pmod, prn); if (random_effects_model(pmod)) { panel_variance_lines(pmod, prn); } else if (pmod->ci != NLS && pmod->aux != AUX_VECM) { Fline(pmod, prn); } if (pmod->ci == PANEL || (pmod->ci == OLS && dataset_is_panel(pdinfo))) { dwline(pmod, prn); } if (dataset_is_time_series(pdinfo)) { if (pmod->ci == OLS || pmod->ci == MPOLS || pmod->ci == VAR || (pmod->ci == WLS && gretl_model_get_int(pmod, "wt_dummy"))) { dwline(pmod, prn); if (pmod->ci != VAR && pmod->aux != AUX_VECM && gretl_model_get_int(pmod, "ldepvar")) { dhline(pmod, prn); } } /* FIXME -- check output below */ if (pmod->ci == TSLS) { dwline(pmod, prn); } } if (pmod->aux != AUX_VECM) { if (pmod->ci == OLS || pmod->ci == MPOLS || fixed_effects_model(pmod)) { print_ll(pmod, prn); } info_stats_lines(pmod, prn); } print_middle_table_end(prn); if (pmod->ci == TSLS && plain_format(prn)) { r_squared_message(pmod, prn); } } else if (pmod->ci == WLS && gretl_model_get_int(pmod, "iters")) { /* panel ML estimation */ print_middle_table_start(prn); depvarstats(pmod, prn); print_ll(pmod, prn); info_stats_lines(pmod, prn); print_middle_table_end(prn); } else if (pmod->ci == MLE) { print_middle_table_start(prn); print_ll(pmod, prn); info_stats_lines(pmod, prn); print_middle_table_end(prn); } else if (pmod->ci == HSK || pmod->ci == ARCH || (pmod->ci == WLS && !gretl_model_get_int(pmod, "wt_dummy"))) { weighted_stats_message(prn); print_middle_table_start(prn); if (essline(pmod, prn)) { print_middle_table_end(prn); goto close_format; } rsqline(pmod, prn); Fline(pmod, prn); if (dataset_is_time_series(pdinfo)) { dwline(pmod, prn); } info_stats_lines(pmod, prn); print_middle_table_end(prn); original_stats_message(prn); print_middle_table_start(prn); depvarstats(pmod, prn); if (essline_original(pmod, prn)) { print_middle_table_end(prn); goto close_format; } print_middle_table_end(prn); } else if (pmod->ci == AR || pmod->ci == CORC || pmod->ci == HILU || pmod->ci == PWE) { rho_differenced_stats_message(prn); print_middle_table_start(prn); if (essline(pmod, prn)) { print_middle_table_end(prn); goto close_format; } rsqline(pmod, prn); Fline(pmod, prn); dwline(pmod, prn); info_stats_lines(pmod, prn); print_middle_table_end(prn); } if (plain_format(prn) && pmod->ci != MLE && pmod->ci != PANEL && pmod->ci != ARMA && pmod->ci != NLS && pmod->ci != GMM && !pmod->aux) { pval_max_line(pmod, pdinfo, prn); } close_format: if (opt & OPT_O) { outcovmx(pmod, pdinfo, prn); } if (any_tests(pmod)) { print_model_tests(pmod, prn); } if (!plain_format(prn)) { model_format_end(prn); } if (gotnan) { pmod->errcode = E_NAN; } return gotnan; } static void print_pval_str (double pval, char *str) { if (pval < .00001) { sprintf(str, "<%.5f", 0.00001); } else { sprintf(str, "%.5f", pval); } } static void plain_print_pval (double pval, PRN *prn) { char pvstr[16]; if (pval < .00001) { sprintf(pvstr, "<%.5f", 0.00001); } else { sprintf(pvstr, "%.5f", pval); } pprintf(prn, "%*s", UTF_WIDTH(pvstr, 10), pvstr); if (pval < 0.01) { pputs(prn, " ***"); } else if (pval < 0.05) { pputs(prn, " **"); } else if (pval < 0.10) { pputs(prn, " *"); } } static void plain_print_tval (double tval, PRN *prn) { if (fabs(tval) >= 1000) { /* || t < .001 ? */ char numstr[9]; sprintf(numstr, "%#8.2G", tval); pprintf(prn, " %8s", numstr); } else if (tval <= -100) { pprintf(prn, " %7.2f", tval); } else { pprintf(prn, " %7.3f", tval); } } static int prepare_model_coeff (const MODEL *pmod, const DATAINFO *pdinfo, int i, model_coeff *mc, PRN *prn) { int gotnan = 0; model_coeff_init(mc); mc->show_pval = !binary_model(pmod) || gretl_model_get_int(pmod, "show-pvals"); if (tex_format(prn)) { make_tex_coeff_name(pmod, pdinfo, i, mc->name); } else { gretl_model_get_param_name(pmod, pdinfo, i, mc->name); } if (xna(pmod->coeff[i])) { gotnan = 1; } else { mc->b = pmod->coeff[i]; } if (!xna(pmod->sderr[i])) { mc->se = pmod->sderr[i]; } if (!na(mc->b) && !na(mc->se) && mc->se > 0.0) { mc->tval = mc->b / mc->se; if (xna(mc->tval)) { mc->tval = NADBL; } } if (mc->show_pval && !na(mc->tval)) { if (pmod->aux == AUX_ADF || pmod->aux == AUX_DF) { if (i + 2 == gretl_model_get_int(pmod, "dfnum")) { mc->pval = gretl_model_get_double(pmod, "dfpval"); } mc->df_pval = 1; } else { mc->pval = coeff_pval(pmod->ci, mc->tval, pmod->dfd); } } if (!gotnan && !mc->show_pval && binary_model(pmod) && pmod->list[i+2] != 0) { double *slopes = gretl_model_get_data(pmod, "slopes"); if (slopes != NULL) { mc->slope = slopes[i]; } } return gotnan; } static void plain_print_coeff (const model_coeff *mc, PRN *prn) { pprintf(prn, " %-15s ", mc->name); if (na(mc->b)) { pprintf(prn, "%*s", UTF_WIDTH(_("undefined"), 17), _("undefined")); } else { gretl_print_value(mc->b, prn); } /* get out if std error is undefined */ if (na(mc->se)) { pprintf(prn, "%*s\n", UTF_WIDTH(_("undefined"), 16), _("undefined")); return; } gretl_print_value(mc->se, prn); if (!na(mc->tval)) { plain_print_tval(mc->tval, prn); } if (!na(mc->slope)) { /* slope for binary models */ gretl_print_value(mc->slope, prn); } else if (mc->show_pval) { if (na(mc->pval)) { if (!mc->df_pval) { pprintf(prn, " %*s", UTF_WIDTH(_("undefined"), 10), _("undefined")); } } else { plain_print_pval(mc->pval, prn); } } pputc(prn, '\n'); } static void rtf_print_double (double xx, PRN *prn) { char numstr[32]; xx = screen_zero(xx); sprintf(numstr, "%.*g", GRETL_DIGITS, xx); gretl_fix_exponent(numstr); pprintf(prn, " \\qc %s\\cell", numstr); } static void rtf_print_coeff (const model_coeff *mc, PRN *prn) { pputs(prn, RTF_COEFF_ROW); pprintf(prn, "\\ql %s\\cell", mc->name); if (na(mc->b)) { pprintf(prn, " \\qc %s\\cell", I_("undefined")); } else { rtf_print_double(mc->b, prn); } if (na(mc->se)) { pprintf(prn, " \\qc %s\\cell", I_("undefined")); pprintf(prn, " \\qc %s\\cell", I_("undefined")); pprintf(prn, " \\qc %s\\cell", I_("undefined")); goto rtf_coeff_getout; } rtf_print_double(mc->se, prn); if (!na(mc->tval)) { pprintf(prn, " \\qc %.4f\\cell", mc->tval); } else { pprintf(prn, " \\qc %s\\cell", I_("undefined")); } if (!na(mc->slope)) { rtf_print_double(mc->slope, prn); } else if (mc->show_pval) { if (na(mc->pval)) { if (mc->df_pval) { pprintf(prn, " \\qc %s\\cell", I_("unknown")); } else { pprintf(prn, " \\qc %s\\cell", I_("undefined")); } } else { char pvalstr[16]; print_pval_str(mc->pval, pvalstr); pprintf(prn, " \\qc %s\\cell", pvalstr); if (mc->pval < 0.01) { pputs(prn, " \\ql ***\\cell"); } else if (mc->pval < 0.05) { pputs(prn, " \\ql **\\cell"); } else if (mc->pval < 0.10) { pputs(prn, " \\ql *\\cell"); } else { pputs(prn, " \\ql \\cell"); } } } rtf_coeff_getout: pputs(prn, " \\intbl \\row\n"); } static void csv_print_coeff (const model_coeff *mc, PRN *prn) { char d = prn_delim(prn); pprintf(prn, "\"%s\"", mc->name); if (na(mc->b)) { pprintf(prn, "%c\"%s\"", d, I_("undefined")); } else { pprintf(prn, "%c%.15g", d, mc->b); } /* get out if std error is undefined */ if (na(mc->se)) { pprintf(prn, "%c\"%s\"\n", d, I_("undefined")); return; } pprintf(prn, "%c%.15g", d, mc->se); if (!na(mc->tval)) { pprintf(prn, "%c%.15g", d, mc->tval); } else { pprintf(prn, "%c\"%s\"\n", d, I_("undefined")); } if (!na(mc->slope)) { /* slope for binary models */ pprintf(prn, "%c%.15g", d, mc->slope); } else if (mc->show_pval) { if (na(mc->pval)) { if (mc->df_pval) { pprintf(prn, "%c\"%s\"\n", d, I_("unknown")); } else { pprintf(prn, "%c\"%s\"\n", d, I_("undefined")); } } else { pprintf(prn, "%c%.15g", d, mc->pval); } } pputc(prn, '\n'); } static void print_mp_coeff (const model_coeff *mc, PRN *prn) { pprintf(prn, " %-*s", VNAMELEN - 1, mc->name); gretl_print_fullwidth_double(mc->b, GRETL_MP_DIGITS, prn); gretl_print_fullwidth_double(mc->se, GRETL_MP_DIGITS, prn); pputc(prn, '\n'); } void print_coeff (const model_coeff *mc, PRN *prn) { if (plain_format(prn)) { plain_print_coeff(mc, prn); } else if (rtf_format(prn)) { rtf_print_coeff(mc, prn); } else if (tex_format(prn)) { tex_print_coeff(mc, prn); } else if (csv_format(prn)) { csv_print_coeff(mc, prn); } } void print_arch_coeffs (const double *a, const double *se, int T, int order, PRN *prn, int aux) { model_coeff mc; int i; if (aux) { pprintf(prn, "\n%s %d\n\n", _("Test for ARCH of order"), order); pputs(prn, _(" PARAMETER ESTIMATE STDERROR" " T STAT P-VALUE\n\n")); } else { gretl_prn_newline(prn); } for (i=0; i<=order; i++) { model_coeff_init(&mc); mc.b = a[i]; mc.se = se[i]; mc.tval = a[i] / se[i]; mc.pval = t_pvalue_2(mc.tval, T - (order + 1)); if (tex_format(prn)) { sprintf(mc.name, "$\\alpha_%d$", i); } else { sprintf(mc.name, "alpha(%d)", i); } print_coeff(&mc, prn); } } static void print_coeff_separator (const char *s, PRN *prn) { if (tex_format(prn)) { /* FIXME */ pputs(prn, "\\\\ \n"); } else { if (s != NULL) { pputc(prn, '\n'); /* FIXME RTF */ print_centered((rtf_format(prn))? I_(s) : _(s), 78, prn); pputc(prn, '\n'); } pputc(prn, '\n'); } } static int print_coefficients (const MODEL *pmod, const DATAINFO *pdinfo, PRN *prn) { const char *sepstr = NULL; int seppos = -1; model_coeff mc; int nc = pmod->ncoeff; int i, err = 0, gotnan = 0; if (pmod->ci == PANEL) { nc = pmod->list[0] - 1; } gretl_model_get_coeff_separator(pmod, &sepstr, &seppos); if (seppos == -1 && pmod->ci == GARCH) { seppos = pmod->list[0] - 4; } pvalue_level(-1); /* Resets pvalue level indicator */ for (i=0; i<nc; i++) { err = prepare_model_coeff(pmod, pdinfo, i, &mc, prn); if (err) gotnan = 1; if (i == seppos) { print_coeff_separator(sepstr, prn); } if (plain_format(prn) && pmod->ci == MPOLS) { print_mp_coeff(&mc, prn); continue; } pvalue_level(mc.pval); /* retains pvalue level indicator */ print_coeff(&mc, prn); } if (pmod->ci == ARCH) { double *a = gretl_model_get_data(pmod, "arch_coeff"); double *se = gretl_model_get_data(pmod, "arch_sderr"); int order = gretl_model_get_int(pmod, "arch_order"); if (a != NULL && se != NULL && order > 0) { print_arch_coeffs(a, se, pmod->nobs, order, prn, 0); } } return gotnan; } static void print_rho (const ARINFO *arinfo, int c, int dfd, PRN *prn) { char ustr[32]; double xx = arinfo->rho[c] / arinfo->sderr[c]; if (plain_format(prn)) { char pvalstr[16]; double pval; sprintf(ustr, "u_%d", arinfo->arlist[c+1]); pprintf(prn, "%14s", ustr); bufspace(3, prn); gretl_print_value (arinfo->rho[c], prn); bufspace(2, prn); gretl_print_value (arinfo->sderr[c], prn); pval = t_pvalue_2(xx, dfd); pprintf(prn, " %7.3f ", xx, pval); print_pval_str(pval, pvalstr); pprintf(prn, "%*s\n", UTF_WIDTH(pvalstr, 12), pvalstr); } else if (tex_format(prn)) { char coeff[32], sderr[32]; tex_dcolumn_double(arinfo->rho[c], coeff); tex_dcolumn_double(arinfo->sderr[c], sderr); sprintf(ustr, "$\\hat{u}_{t-%d}$", arinfo->arlist[c+1]); pprintf(prn, "%s &\n" " %s &\n" " %s &\n" " %.4f &\n" " %.4f \\\\\n", ustr, coeff, sderr, arinfo->rho[c] / arinfo->sderr[c], t_pvalue_2(xx, dfd)); } else if (rtf_format(prn)) { char pvalstr[16]; double pval; pputs(prn, RTF_COEFF_ROW); pprintf(prn, "\\ql u(-%d)\\cell", arinfo->arlist[c+1]); rtf_print_double(arinfo->rho[c], prn); rtf_print_double(arinfo->sderr[c], prn); pprintf(prn, " \\qc %.4f\\cell", xx); pval = t_pvalue_2(xx, dfd); print_pval_str(pval, pvalstr); pprintf(prn, " \\qc %s\\cell", pvalstr); if (pval < 0.01) { pputs(prn, " \\ql ***\\cell"); } else if (pval < 0.05) { pputs(prn, " \\ql **\\cell"); } else if (pval < 0.10) { pputs(prn, " \\ql *\\cell"); } else { pputs(prn, " \\ql \\cell"); } pputs(prn, " \\intbl \\row\n"); } } static void print_rho_terms (const MODEL *pmod, PRN *prn) { int i, dfd; double xx = 0.0; if (pmod->arinfo == NULL || pmod->arinfo->arlist == NULL || pmod->arinfo->rho == NULL || pmod->arinfo->sderr == NULL) { return; } if (plain_format(prn)) { pprintf(prn, "\n%s:\n\n", _("Estimates of the AR coefficients")); } if (pmod->arinfo->arlist[0] > 1) { dfd = pmod->dfd + (pmod->ncoeff - pmod->arinfo->arlist[0]); } else { dfd = pmod->dfd; } for (i=1; i<=pmod->arinfo->arlist[0]; i++) { print_rho(pmod->arinfo, i - 1, dfd, prn); xx += pmod->arinfo->rho[i-1]; } if (pmod->arinfo->arlist[0] > 1 && plain_format(prn)) { pprintf(prn, "\n%s = %#g\n\n", _("Sum of AR coefficients"), xx); } } static void tex_float_str (double x, char *str) { if (x < 0.) { strcpy(str, "$-$"); sprintf(str + 3, "%.*g", GRETL_DIGITS, -x); } else { sprintf(str, "%.*g", GRETL_DIGITS, x); } } const char *roots_hdr = N_(" Real Imaginary" " Modulus Frequency"); const char *root_fmt = "%8s%3d%17.4f%11.4f%11.4f%11.4f\n"; const char *roots_sep = " -----------------------------------------" "------------------"; static void print_root (double rx, double ix, double mod, double fr, int i, int hline, PRN *prn) { if (plain_format(prn)) { pprintf(prn, root_fmt, _("Root"), i, rx, ix, mod, fr); } else if (tex_format(prn)) { pprintf(prn, "& %s & %d & $%.4f$ & $%.4f$ & $%.4f$ & $%.4f$ \\\\ ", I_("Root"), i, rx, ix, mod, fr); if (hline) { pputs(prn, "\\hline\n"); } else { pputc(prn, '\n'); } } else if (rtf_format(prn)) { pputs(prn, RTF_ROOT_ROW); pprintf(prn, "\\ql \\cell \\ql %s %d \\cell" " \\qr %.4f\\cell" " \\qr %.4f\\cell" " \\qr %.4f\\cell" " \\qr %.4f\\cell \\intbl \\row\n", I_("Root"), i, rx, ix, mod, fr); } } static void root_start (const char *tag, PRN *prn) { if (plain_format(prn)) { pprintf(prn, " %s\n", _(tag)); } else if (tex_format(prn)) { pprintf(prn, "%s \\\\ \n", I_(tag)); } else if (rtf_format(prn)) { pputs(prn, RTF_ROOT_ROW); pprintf(prn, "\\ql %s\\cell\\ql \\cell\\ql \\cell\\ql \\cell\\ql \\cell" "\\ql\\cell \\intbl \\row\n", I_(tag)); } } static void print_arma_roots (const MODEL *pmod, PRN *prn) { cmplx *roots = gretl_model_get_data(pmod, "roots"); if (roots != NULL) { int p = arma_model_nonseasonal_AR_order(pmod); int q = arma_model_nonseasonal_MA_order(pmod); int P = gretl_model_get_int(pmod, "arma_P"); int Q = gretl_model_get_int(pmod, "arma_Q"); int i, k, hline; double mod, fr; if (plain_format(prn)) { pprintf(prn, "\n%s\n%s\n", _(roots_hdr), roots_sep); } else if (tex_format(prn)) { pputs(prn, "\n\\vspace{1em}\n\n"); pputs(prn, "\\begin{tabular}{llrrrrr}\n"); pprintf(prn, "& & & %s & %s & %s & %s \\\\ \\hline\n", I_("Real"), I_("Imaginary"), I_("Modulus"), I_("Frequency")); } else if (rtf_format(prn)) { pputs(prn, "\n\\par\n{" RTF_ROOT_ROW); pprintf(prn, "\\qr \\cell \\qc \\cell" " \\qc {\\i %s}\\cell" " \\qc {\\i %s}\\cell" " \\qc {\\i %s}\\cell" " \\qc {\\i %s}\\cell \\intbl \\row\n", I_("Real"), I_("Imaginary"), I_("Modulus"), I_("Frequency")); } if (p > 0) { k = 1; root_start(N_("AR"), prn); for (i=0; i<p; i++) { if (roots[i].i != 0) { mod = roots[i].r * roots[i].r + roots[i].i * roots[i].i; mod = sqrt(mod); } else { mod = fabs(roots[i].r); } fr = atan2(roots[i].i, roots[i].r) / M_2PI; if (i == p - 1 && q == 0 && P == 0 && Q == 0) { hline = 1; } else { hline = 0; } print_root(roots[i].r, roots[i].i, mod, fr, k++, hline, prn); } } if (P > 0) { k = 1; root_start(N_("AR (seasonal)"), prn); for (i=p; i<p+P; i++) { if (roots[i].i != 0) { mod = roots[i].r * roots[i].r + roots[i].i * roots[i].i; mod = sqrt(mod); } else { mod = fabs(roots[i].r); } fr = atan2(roots[i].i, roots[i].r) / M_2PI; if (i == p + P - 1 && q == 0 && Q == 0) { hline = 1; } else { hline = 0; } print_root(roots[i].r, roots[i].i, mod, fr, k++, hline, prn); } } if (q > 0) { k = 1; root_start(N_("MA"), prn); for (i=p+P; i<p+P+q; i++) { if (roots[i].i != 0) { mod = roots[i].r * roots[i].r + roots[i].i * roots[i].i; mod = sqrt(mod); } else { mod = fabs(roots[i].r); } fr = atan2(roots[i].i, roots[i].r) / M_2PI; if (i == p + P + q - 1 && Q == 0) { hline = 1; } else { hline = 0; } print_root(roots[i].r, roots[i].i, mod, fr, k++, hline, prn); } } if (Q > 0) { k = 1; root_start(N_("MA (seasonal)"), prn); for (i=p+P+q; i<p+P+q+Q; i++) { if (roots[i].i != 0) { mod = roots[i].r * roots[i].r + roots[i].i * roots[i].i; mod = sqrt(mod); } else { mod = fabs(roots[i].r); } fr = atan2(roots[i].i, roots[i].r) / M_2PI; if (i == p + P + q + Q - 1) { hline = 1; } else { hline = 0; } print_root(roots[i].r, roots[i].i, mod, fr, k++, hline, prn); } } if (plain_format(prn)) { pprintf(prn, "%s\n\n", roots_sep); } else if (tex_format(prn)) { pputs(prn, "\\end{tabular}\n"); } else if (rtf_format(prn)) { pputs(prn, "}\n"); } } } static void print_tobit_stats (const MODEL *pmod, PRN *prn) { int cenc = gretl_model_get_int(pmod, "censobs"); double cenpc = 100.0 * cenc / pmod->nobs; if (plain_format(prn)) { pprintf(prn, " %s: %d (%.1f%%)\n", _("Censored observations"), cenc, cenpc); pprintf(prn, " %s = %.*g\n", _("sigma"), GRETL_DIGITS, pmod->sigma); } else if (rtf_format(prn)) { pprintf(prn, RTFTAB "%s: %d (%.1f%%)\n", I_("Censored observations"), cenc, cenpc); pprintf(prn, RTFTAB "%s = %g\n", I_("sigma"), pmod->sigma); } else if (tex_format(prn)) { char xstr[32]; pprintf(prn, "%s & \\multicolumn{1}{r}{%.1f\\%%} \\\\\n", I_("Censored observations"), cenpc); tex_dcolumn_double(pmod->sigma, xstr); pprintf(prn, "$\\hat{\\sigma}$ & %s \\\\\n", xstr); } } static void print_heckit_stats (const MODEL *pmod, PRN *prn) { int totobs = gretl_model_get_int(pmod, "totobs"); int cenobs = totobs - pmod->nobs; double cenpc = 100.0 * cenobs / totobs; if (plain_format(prn)) { pprintf(prn, " %s: %d\n", _("Total observations"), totobs); pprintf(prn, " %s: %d (%.1f%%)\n", _("Censored observations"), cenobs, cenpc); pprintf(prn, " %s = %.*g\n", _("sigma"), GRETL_DIGITS, pmod->sigma); } else if (rtf_format(prn)) { pprintf(prn, RTFTAB "%s: %d\n", I_("Total observations"), totobs); pprintf(prn, RTFTAB "%s: %d (%.1f%%)\n", I_("Censored observations"), cenobs, cenpc); pprintf(prn, RTFTAB "%s = %g\n", I_("sigma"), pmod->sigma); } else if (tex_format(prn)) { char xstr[32]; pprintf(prn, "%s & \\multicolumn{1}{r}{%d} \\\\\n", I_("Total observations"), totobs); pprintf(prn, "%s & \\multicolumn{1}{r}{%.1f\\%%} \\\\\n", I_("Censored observations"), cenpc); tex_dcolumn_double(pmod->sigma, xstr); pprintf(prn, "$\\hat{\\sigma}$ & %s \\\\\n", xstr); } } static void print_poisson_offset (const MODEL *pmod, const DATAINFO *pdinfo, PRN *prn) { int offvar = gretl_model_get_int(pmod, "offset_var"); if (offvar > 0) { char namestr[24]; sprintf(namestr, "log(%s)", pdinfo->varname[offvar]); if (plain_format(prn)) { pprintf(prn, "\n %13s 1.0\n", namestr); } else if (rtf_format(prn)) { pputs(prn, RTF_COEFF_ROW); pprintf(prn, "\\ql %s\\cell\\qc 1.0\\cell", namestr); pputs(prn, "\\qc \\cell\\qc \\cell \\qc \\cell \\intbl \\row\n"); } else if (tex_format(prn)) { char tmp[32]; tex_escape(tmp, namestr); pprintf(prn, "{\\rm %s} & \\multicolumn{1}{c}{1.0} \\\\\n", tmp); } } } static void print_arma_stats (const MODEL *pmod, PRN *prn) { double mu = gretl_model_get_double(pmod, "mean_error"); double var = pmod->sigma * pmod->sigma; if (plain_format(prn)) { pprintf(prn, " %s = %.*g\n", _("Mean of innovations"), GRETL_DIGITS, mu); pprintf(prn, " %s = %.*g\n", _("Variance of innovations"), GRETL_DIGITS, var); } else if (rtf_format(prn)) { pprintf(prn, RTFTAB "%s = %g\n", I_("Mean of innovations"), mu); pprintf(prn, RTFTAB "%s = %g\n", I_("Variance of innovations"), var); } else if (tex_format(prn)) { char xstr[32]; tex_dcolumn_double(mu, xstr); pprintf(prn, "%s & %s \\\\\n", I_("Mean of innovations"), xstr); tex_dcolumn_double(var, xstr); pprintf(prn, "%s & %s \\\\\n", I_("Variance of innovations"), xstr); } } static void plain_print_act_pred (const int *ap, PRN *prn) { int leftlen; int numwidth = 1; int i, bign = 0; for (i=0; i<4; i++) { if (ap[i] > bign) { bign = ap[i]; } } while (bign /= 10) { numwidth++; } leftlen = strlen(_("Actual")) + 3; /* utflen */ bufspace(leftlen + 2, prn); pputs(prn, _("Predicted")); pputc(prn, '\n'); bufspace(leftlen + 3, prn); pprintf(prn, "%*d %*d\n", numwidth, 0, numwidth, 1); bufspace(2, prn); pputs(prn, _("Actual")); pprintf(prn, " 0 %*d %*d\n", numwidth, ap[0], numwidth, ap[1]); bufspace(leftlen, prn); pprintf(prn, "1 %*d %*d\n", numwidth, ap[2], numwidth, ap[3]); pputc(prn, '\n'); } static void print_binary_statistics (const MODEL *pmod, const DATAINFO *pdinfo, PRN *prn) { int slopes = !gretl_model_get_int(pmod, "show-pvals"); double model_chisq = gretl_model_get_double(pmod, "chisq"); const double *crit = pmod->criterion; const int *act_pred; int correct = -1; double pc_correct = NADBL; int i; act_pred = gretl_model_get_data(pmod, "discrete_act_pred"); if (act_pred != NULL) { correct = act_pred[0] + act_pred[3]; pc_correct = 100 * (double) correct / pmod->nobs; } if (plain_format(prn)) { pprintf(prn, " %s %s = %.3f\n", _("Mean of"), pdinfo->varname[pmod->list[1]], pmod->ybar); if (correct >= 0) { pprintf(prn, " %s = %d (%.1f%%)\n", _("Number of cases 'correctly predicted'"), correct, pc_correct); } pprintf(prn, " f(beta'x) %s = %.3f\n", _("at mean of independent vars"), pmod->sdy); pseudorsqline(pmod, prn); pprintf(prn, " %s = %g\n", _("Log-likelihood"), pmod->lnL); if (pmod->aux != AUX_OMIT && pmod->aux != AUX_ADD) { i = pmod->ncoeff - 1; pprintf(prn, " %s: %s(%d) = %g (%s %f)\n", _("Likelihood ratio test"), _("Chi-square"), i, model_chisq, _("p-value"), chisq_cdf_comp(model_chisq, i)); } pprintf(prn, " %s (%s) = %g\n", _(aic_str), _(aic_abbrev), crit[C_AIC]); pprintf(prn, " %s (%s) = %g\n", _(bic_str), _(bic_abbrev), crit[C_BIC]); pprintf(prn, " %s (%s) = %g\n", _(hqc_str), _(hqc_abbrev), crit[C_HQC]); pputc(prn, '\n'); if (act_pred != NULL) { plain_print_act_pred(act_pred, prn); } } else if (rtf_format(prn)) { pputc(prn, '\n'); if (slopes) { pprintf(prn, "\\par {\\super *}%s\n", I_("Evaluated at the mean")); } pprintf(prn, "\\par %s %s = %.3f\n", I_("Mean of"), pdinfo->varname[pmod->list[1]], pmod->ybar); if (correct >= 0) { pprintf(prn, "\\par %s = %d (%.1f%%)\n", I_("Number of cases 'correctly predicted'"), correct, pc_correct); } pprintf(prn, "\\par f(beta'x) %s = %.3f\n", I_("at mean of independent vars"), pmod->sdy); pseudorsqline(pmod, prn); pprintf(prn, "\\par %s = %g\n", I_("Log-likelihood"), pmod->lnL); if (pmod->aux != AUX_OMIT && pmod->aux != AUX_ADD) { i = pmod->ncoeff - 1; pprintf(prn, "\\par %s: %s(%d) = %g (%s %f)\n", I_("Likelihood ratio test"), I_("Chi-square"), i, model_chisq, I_("p-value"), chisq_cdf_comp(model_chisq, i)); } pprintf(prn, "\\par %s (%s) = %g\n", I_(aic_str), I_(aic_abbrev), crit[C_AIC]); pprintf(prn, "\\par %s (%s) = %g\\par\n", I_(bic_str), I_(bic_abbrev), crit[C_BIC]); pprintf(prn, "\\par %s (%s) = %g\\par\n", I_(hqc_str), I_(hqc_abbrev), crit[C_HQC]); pputc(prn, '\n'); } else if (tex_format(prn)) { char lnlstr[16]; if (slopes) { pprintf(prn, "\\begin{center}\n$^*$%s\n\\end{center}\n", I_("Evaluated at the mean")); } pputs(prn, "\\vspace{1em}\n\\begin{raggedright}\n"); pprintf(prn, "%s %s = %.3f\\\\\n", I_("Mean of"), pdinfo->varname[pmod->list[1]], pmod->ybar); if (correct >= 0) { pprintf(prn, "%s = %d (%.1f percent)\\\\\n", I_("Number of cases `correctly predicted'"), correct, pc_correct); } pseudorsqline(pmod, prn); pprintf(prn, "$f(\\beta'x)$ %s = %.3f\\\\\n", I_("at mean of independent vars"), pmod->sdy); tex_float_str(pmod->lnL, lnlstr); pprintf(prn, "%s = %s\\\\\n", I_("Log-likelihood"), lnlstr); if (pmod->aux != AUX_OMIT && pmod->aux != AUX_ADD) { i = pmod->ncoeff - 1; pprintf(prn, "%s: $\\chi^2_{%d}$ = %.3f (%s %f)\\\\\n", I_("Likelihood ratio test"), i, model_chisq, I_("p-value"), chisq_cdf_comp(model_chisq, i)); } pprintf(prn, "%s (%s) = %g\\\\\n", I_(aic_str), I_(aic_abbrev), crit[C_AIC]); pprintf(prn, "%s (%s) = %g\\\\\n", I_(bic_str), I_(bic_abbrev), crit[C_BIC]); pprintf(prn, "%s (%s) = %g\\\\\n", I_(tex_hqc_str), I_(hqc_abbrev), crit[C_HQC]); pputs(prn, "\\end{raggedright}\n"); } } int ols_print_anova (const MODEL *pmod, PRN *prn) { double mst, msr, mse, rss; if (pmod->ci != OLS || !pmod->ifc || na(pmod->ess) || na(pmod->tss)) { return 1; } pprintf(prn, "%s:\n\n", _("Analysis of Variance")); rss = pmod->tss - pmod->ess; pprintf(prn, "%35s %8s %16s\n\n", _("Sum of squares"), _("df"), _("Mean square")); msr = rss / pmod->dfn; pprintf(prn, " %-16s %16g %8d %16g\n", _("Regression"), rss, pmod->dfn, msr); mse = pmod->ess / pmod->dfd; pprintf(prn, " %-16s %16g %8d %16g\n", _("Residual"), pmod->ess, pmod->dfd, mse); mst = pmod->tss / pmod->dfd; pprintf(prn, " %-16s %16g %8d %16g\n", _("Total"), pmod->tss, pmod->nobs - 1, mst); pprintf(prn, "\n R^2 = %g / %g = %.6f\n", rss, pmod->tss, rss / pmod->tss); if (pmod->ess == 0) { pprintf(prn, " F(%d, %d) = %g / %g (%s)\n\n", pmod->dfn, pmod->dfd, msr, mse, _("undefined")); } else { pprintf(prn, " F(%d, %d) = %g / %g = %g\n\n", pmod->dfn, pmod->dfd, msr, mse, msr / mse); } return 0; }