Re: [Gretl-users] ANOVA
by andreas.rosenblad＠ltv.se

geno83(a)gmail.com @ wrote 2008-04-17 19:12:44 :
> Hello
>
> I'm working on ANOVA. I want put one way Anova and two way Anova to
gretl.
> I made first version of one way ANOVA. It is still test version, but
> it's working.
> You can download sources and test it.
> I will be glad if you put ANOVA to gretl official version.
>
Very good. ANOVA is one of the features I have missed in gretl. I hope that
you will continue to contribute code to gretl.
Best regards,
Andreas
14 years, 6 months

heckit two-step results
by Michael A Coon

The Heckit two-step command returns estimates for rho and sigma. Can anybody tell me the significance of these estimates?
Mike Coon
macoon(a)uwm.edu
14 years, 10 months

graph display on Mac OS X
by Daniel Hinderink

hi List,
I installed gretl and also Aquaterm and gnuplot on my mac.
Gretl works except when it comes to display of diagrammes.
That displays an error message "no such file or directory".
Any hints?
thank you,
Daniel
14 years, 10 months

t-stats and p-values after mle
by Stefano Balietti

Is there any accessor to catch the matrix of the p-values and the
matrix of the t stats after performing a ml estimation? $test and
$pvalues don't seem to make my case, as they return a scalar and
anyway they are not filled by the mle command. Maybe they should be
able to return a matrix as well.
Cheers,
Stefano
14 years, 10 months

please test!
by Allin Cottrell

We've had some useful bug reports lately, and I'd just like to
urge anyone who has discovered anything that's not right in gretl
to report sooner rather than later, either here or via the
sourceforge bug-tracker.
The more bugs we can fix before the 1.7.5 release, the better. I
have a feeling this release will be a "keeper". We've fixed a lot
of things lately (besides adding various goodies), and while some
of these were newly introduced bugs, or bugs in newly introduced
features, I believe the bug count must now be substantially lower
than in 1.7.4.
Allin Cottrell
14 years, 10 months

LM Tests in systems
by Mixon, Wilson

Using the dialog box, I can conduct autocorr & arch tests for the equations in a system. Using the following commands, I get the message below.
system name = FullModel
equation 6 0 10 28 11 16 18 24
equation 7 0 10 28 11 17 18 25
equation 8 0 10 28 11 16 19 26
equation 9 0 10 28 11 17 19 27
end system
estimate FullModel method = sur
lmtest --arch --quiet
? lmtest --arch --quiet
Sorry, command not available for this estimator
Suggestions?
14 years, 10 months

GARCH estimation
by yinung CYCU

Dear all
I use gretl 1.7.4 to estimate a GARCH model by using default menu function
(i.e., \Model\Time series\GARCH ) and by the command in console. But they
generate different results. The details of iterations are as follows. Any
idea?
==== results by menu=====
Automatic initialization of parameters
Regression coefficients:
theta[0] = 0.0511825
theta[1] = 1.08508
Variance parameters:
alpha[0] = 0.1
beta[0] = 0.9
Iteration 1: Log-likelihood = -168.929078042
Parameters: 0.11038 1.0851 0.10000 0.90000
Gradients: -26.738 17.074 481.64 14.243
Iteration 2: Log-likelihood = -139.605272823 (steplength = 0.0016)
Parameters: 0.067597 1.1124 0.87063 0.92279
Gradients: -4.4061 0.82275 -15.175 -8.1703
Iteration 3: Log-likelihood = -138.361721087 (steplength = 0.04)
Parameters: -0.13607 1.1652 0.87232 0.62335
Gradients: 14.823 -0.51238 -14.088 -6.9177
Iteration 4: Log-likelihood = -137.371894269 (steplength = 0.008)
Parameters: -0.12485 1.1848 0.87847 0.47302
Gradients: 13.892 -1.0676 -13.148 -5.2299
Iteration 5: Log-likelihood = -137.147777193 (steplength = 0.04)
Parameters: -0.12168 1.1207 0.88177 0.43192
Gradients: 13.651 0.40209 -12.854 -4.5731
Iteration 6: Log-likelihood = -136.065550003 (steplength = 0.2)
Parameters: -0.055939 1.1709 0.88165 0.29403
Gradients: 7.6020 -1.0743 -11.185 -0.64410
Iteration 7: Log-likelihood = -135.589722350 (steplength = 1)
Parameters: 0.054295 1.1305 0.86108 0.32088
Gradients: -3.2400 -0.48930 -11.296 -1.6096
Iteration 8: Log-likelihood = -135.332923963 (steplength = 1)
Parameters: 0.044387 1.1121 0.84171 0.26964
Gradients: -2.1320 -0.080313 -9.7947 0.99314
Iteration 9: Log-likelihood = -134.612248244 (steplength = 1)
Parameters: 0.014804 1.0933 0.76024 0.27015
Gradients: 0.83895 0.60996 -7.3230 3.3510
Iteration 10: Log-likelihood = -133.876720666 (steplength = 1)
Parameters: -0.034438 1.0938 0.46226 0.40605
Gradients: 6.1180 0.99752 10.528 6.9157
Iteration 11: Log-likelihood = -133.215756120 (steplength = 0.008)
Parameters: 0.014505 1.1018 0.54648 0.46137
Gradients: -0.55270 0.72059 -1.2327 0.43556
Iteration 12: Log-likelihood = -133.185323523 (steplength = 0.04)
Parameters: 0.010238 1.1316 0.52856 0.49641
Gradients: -0.25051 -0.14061 -0.71733 -0.28480
Iteration 13: Log-likelihood = -133.185060907 (steplength = 0.008)
Parameters: 0.011028 1.1308 0.52769 0.49709
Gradients: -0.36195 -0.11592 -0.65345 -0.28715
Iteration 14: Log-likelihood = -133.185045046 (steplength = 0.04)
Parameters: 0.0087095 1.1249 0.52597 0.50187
Gradients: -0.053499 0.085396 -0.65223 -0.41383
Iteration 15: Log-likelihood = -133.181789118 (steplength = 1)
Parameters: 0.0081963 1.1273 0.52065 0.49465
Gradients: -0.016645 -0.0072318 0.043542 -0.00045134
Iteration 16: Log-likelihood = -133.181774062 (steplength = 1)
Parameters: 0.0081232 1.1271 0.52128 0.49410
Gradients: -0.00074809 -0.00035241 -0.0012373 0.00028761
Iteration 17: Log-likelihood = -133.181774041 (steplength = 1)
Parameters: 0.0081164 1.1271 0.52126 0.49413
Gradients: 6.7268e-006 4.3038e-006-1.6833e-005-1.9424e-005
Iteration 17: Log-likelihood = -133.181774041 (steplength = 1)
Parameters: 0.0081164 1.1271 0.52126 0.49413
Gradients: 6.7268e-006 4.3038e-006-1.6833e-005-1.9424e-005
--- FINAL VALUES:
Log-likelihood = -133.181774041 (steplength = 6.4e-005)
Parameters: 0.0081164 1.1271 0.52126 0.49413
Gradients: 6.7268e-006 4.3038e-006-1.6833e-005-1.9424e-005
theta[0]: 0.00381941 (0.0406031)
theta[1]: 0.530368 (0.0834569)
theta[2]: 0.115430 (0.0264921)
theta[3]: 0.494127 (0.192625)
Function evaluations: 47
Evaluations of gradient: 17
Model 11: GARCH estimates using the 99 observations 1980:02-1988:04
Dependent variable: Y
Standard errors based on Hessian
VARIABLE COEFFICIENT STDERROR T STAT P-VALUE
const 0.00381941 0.0406031 0.094 0.92506
Y_1 0.530368 0.0834569 6.355 <0.00001 ***
alpha(0) 0.115430 0.0264921 4.357 0.00001 ***
alpha(1) 0.494127 0.192625 2.565 0.01031 **
Mean of dependent variable = 0.0519415
Standard deviation of dep. var. = 0.544934
Unconditional error variance = 0.22818
Log-likelihood = -58.5562
Akaike information criterion (AIC) = 127.112
Schwarz Bayesian criterion (BIC) = 140.088
Hannan-Quinn criterion (HQC) = 132.362
==== results by the command in console=====
? garch 0 1; Y Y(-1) --verbose
Automatic initialization of parameters
Regression coefficients:
theta[0] = 0.0511825
theta[1] = 1.08508
Variance parameters:
alpha[0] = 0.1
beta[0] = 0.9
Iteration 1: Log-likelihood = -270.911199903
Parameters: 0.11038 1.0851 0.10000 0.90000
Gradients: -125.16 -125.16 1010.7 30.388
Iteration 2: Log-likelihood = -170.537739660 (steplength = 0.0016)
Parameters: -0.089875 0.88483 1.7171 0.94862
Gradients: -25.749 -25.749 -8.7587 -8.4495
Iteration 3: Log-likelihood = -161.761522666 (steplength = 0.008)
Parameters: -0.29926 0.67545 1.6788 0.88214
Gradients: -11.183 -11.183 -10.840 -8.8715
Iteration 4: Log-likelihood = -158.391619816 (steplength = 0.04)
Parameters: -0.31167 0.66303 1.6896 0.51071
Gradients: -10.407 -10.407 -10.879 -8.1069
Iteration 5: Log-likelihood = -157.154680098 (steplength = 0.04)
Parameters: -0.31888 0.65583 1.6928 0.36062
Gradients: -10.000 -10.000 -10.621 -6.6638
Iteration 6: Log-likelihood = -155.742679661 (steplength = 0.2)
Parameters: -0.35479 0.61992 1.6858 0.22820
Gradients: -7.1755 -7.1755 -10.191 -3.8497
Iteration 7: Log-likelihood = -154.844791246 (steplength = 1)
Parameters: -0.48452 0.49018 1.6370 0.10641
Gradients: 5.3640 5.3640 -8.7104 3.1207
Iteration 8: Log-likelihood = -154.573226547 (steplength = 1)
Parameters: -0.45621 0.51850 1.6312 0.19907
Gradients: 2.1978 2.1978 -10.062 -2.3733
Iteration 9: Log-likelihood = -154.393792855 (steplength = 1)
Parameters: -0.41196 0.56275 1.6201 0.14415
Gradients: -2.0434 -2.0434 -9.3522 0.38397
Iteration 10: Log-likelihood = -153.968693027 (steplength = 1)
Parameters: -0.42290 0.55181 1.5786 0.15683
Gradients: -0.97944 -0.97944 -9.3680 0.21026
Iteration 11: Log-likelihood = -150.992406742 (steplength = 0.04)
Parameters: -0.46207 0.51263 1.2039 0.16524
Gradients: 3.4088 3.4088 -6.1548 7.6249
Iteration 12: Log-likelihood = -148.359103161 (steplength = 0.008)
Parameters: -0.43062 0.54409 0.75562 0.32000
Gradients: -2.3822 -2.3822 1.9263 6.8635
Iteration 13: Log-likelihood = -148.097032678 (steplength = 0.008)
Parameters: -0.45911 0.51560 0.71943 0.36973
Gradients: 0.75946 0.75946 1.8664 4.7097
Iteration 14: Log-likelihood = -147.949161098 (steplength = 1)
Parameters: -0.45122 0.52348 0.75142 0.44913
Gradients: -0.66911 -0.66911 -1.6394 -0.55287
Iteration 15: Log-likelihood = -147.921370789 (steplength = 1)
Parameters: -0.45617 0.51854 0.69072 0.47194
Gradients: -0.69320 -0.69320 0.78234 -0.15366
Iteration 16: Log-likelihood = -147.911096499 (steplength = 1)
Parameters: -0.46083 0.51388 0.71098 0.45901
Gradients: 0.15242 0.15242 -0.086460 0.020146
Iteration 17: Log-likelihood = -147.910849840 (steplength = 1)
Parameters: -0.45975 0.51495 0.70935 0.46012
Gradients: -0.0033672 -0.0033672 -0.010763 -0.0083438
Iteration 18: Log-likelihood = -147.910848410 (steplength = 1)
Parameters: -0.45979 0.51491 0.70914 0.46007
Gradients: 0.00068169 0.00068169 0.00046165 -0.00074704
Iteration 19: Log-likelihood = -147.910848385 (steplength = 1)
Parameters: -0.45979 0.51492 0.70917 0.46004
Gradients: 8.9567e-005 8.9567e-005 8.2642e-006 -0.00017120
Iteration 20: Log-likelihood = -147.910848385 (steplength = 0.008)
Parameters: -0.45979 0.51492 0.70917 0.46004
Gradients: 1.1075e-005 1.1075e-005 4.6432e-005 -0.00012421
Iteration 21: Log-likelihood = -147.910848385 (steplength = 0.008)
Parameters: -0.45979 0.51492 0.70917 0.46004
Gradients: 5.2761e-005 5.2761e-005 3.4521e-005-8.0059e-005
Iteration 22: Log-likelihood = -147.910848385 (steplength = 0.008)
Parameters: -0.45979 0.51492 0.70917 0.46004
Gradients: 4.1306e-005 4.1306e-005 5.3314e-006-9.2102e-005
Iteration 23: Log-likelihood = -147.910848385 (steplength = 1)
Parameters: -0.45978 0.51492 0.70917 0.46003
Gradients: -2.4463e-006-2.4463e-006 2.1778e-006 7.0214e-006
Iteration 23: Log-likelihood = -147.910848385 (steplength = 1)
Parameters: -0.45978 0.51492 0.70917 0.46003
Gradients: -2.4463e-006-2.4463e-006 2.1778e-006 7.0214e-006
--- FINAL VALUES:
Log-likelihood = -147.910848385 (steplength = 0.0016)
Parameters: -0.45978 0.51492 0.70917 0.46003
Gradients: -2.4463e-006-2.4463e-006 2.1778e-006 7.0214e-006
theta[0]: -0.216364 (0.171258)
theta[1]: 0.242311 (0.0635179)
theta[2]: 0.157041 (0.0421745)
theta[3]: 0.460033 (0.177473)
Function evaluations: 58
Evaluations of gradient: 23
Model 10: GARCH estimates using the 99 observations 1980:02-1988:04
Dependent variable: Y
Standard errors based on Hessian
VARIABLE COEFFICIENT STDERROR T STAT P-VALUE
const -0.216364 0.171258 -1.263 0.20645
Y_1 0.242311 0.0635179 3.815 0.00014 ***
alpha(0) 0.157041 0.0421745 3.724 0.00020 ***
alpha(1) 0.460033 0.177473 2.592 0.00954 ***
Mean of dependent variable = 0.0519415
Standard deviation of dep. var. = 0.544934
Unconditional error variance = 0.290835
Log-likelihood = -73.2853
Akaike information criterion (AIC) = 156.571
Schwarz Bayesian criterion (BIC) = 169.546
Hannan-Quinn criterion (HQC) = 161.82
14 years, 10 months

Input data problem
by Krzysztof Dmytrów

Greetings
I have a problem with GRETL 1.7.1 installed from Ubuntu 8.04
repositories. I can open data saved in previous GRETL version from
Ubuntu repositories 1.6.5, I can also open and work on data that was
created under Windows. But when I try to create new data set or when I
try to modify existing data set, I cannot input numbers with decimal
places. When I try to input dot "." as decimall separator or comma
",", in both cases I get the same error message: Extraneous character
',' in data. I would like to say that I created the data in Polish
version of GRETL with "," separator. Here I cannot use neithet "." or
",". I would be extremely grateful for any help.
Krzysztof
14 years, 10 months

Problem with series...
by Mariusz Doszyń

Hello...
I've got identity matrix D=I(16,16) and can't create series from columns by means of (for example) such a command: series d1=D[,1]. I've got data file with 16 observations (spatial data) and using Gretl 1.7.2 (Windows version)... Thanks for help...
Best wishes...
Mariusz
Poland
14 years, 10 months