[Gretl-users] Question on package thres_infer

Hi all, especially Sven, I was playing with the package thres_infer, and it appears that the threshold estimates from functions H_thresh_test() and H_thresh_estim() differ. Is it intented? Should they be the same? In the particular example from the sample script, which I pasted below, the values are similar, but I run it with data that give totally different results. Any thought - suggestions? Best regards, Andreas gretl version 2024d Current session: 2025-04-08 16:37 # Sample script for thresh_infer Read datafile C:\Program Files\gretl\data\misc\denmark.gdt periodicity: 4, maxobs: 55 observations range: 1974:1 to 1987:3 Listing 5 variables:   0) const    1) LRM      2) LRY      3) IBO      4) IDE     Test of Null of No Threshold Against Alternative of Threshold Under Maintained Assumption of Homoskedastic Errors Number of Bootstrap Replications: 1000 Trimming percentage: 0.150000 Threshold Estimate: 0.088000  (46 % of obs in 1st regime) LM-test for no threshold: 4.154898 Bootstrap p-value: 0.923000 ******************************************* Threshold regression based on Hansen (2000) User choice: assume homoskedasticity ******************************************* Global OLS Estimation, Without Threshold Dependent Variable: mg OLS Standard Errors Reported              coefficient   std. error      z      p-value   -------------------------------------------------------   Constant    0.0705718    0.0272334     2.591    0.0096  ***   IBO        -0.469693     0.229408     -2.047    0.0406  **   IDE         0.110332     0.500081      0.2206   0.8254   Observations = 54   Degrees of Freedom = 51   Sum of Squared Errors = 0.0487311   Residual Variance = 0.000955512   R-squared = 0.162774   Heterosked. test p-val = 0.365732 ************************************************************* Threshold Estimation, dependent variable: mg Threshold Variable: IDE Threshold Estimate = 0.074    90% CI: [0.074, 0.11] Sum of Sq. Errors = 0.0435625    Residual Var. = 0.000907553 Joint R-squared = 0.252 Heterosked. test p-value: 0.225 ************************************************************* Regime 1: IDE <= 0.074000  (standard errors do not take into account threshold uncertainty)              coefficient   std. error      z      p-value   -------------------------------------------------------   Constant    -0.833454     0.386015    -2.159    0.0308  **   IBO         -0.774593     0.915857    -0.8458   0.3977   IDE         13.4116       6.06844      2.210    0.0271  **   Observations = 5   Degrees of Freedom = 2   Sum of Squared Errors = 0.00612267   Residual Variance = 0.00306133   R-squared = 0.425631 Regime 2: IDE > 0.074000  (standard errors do not take into account threshold uncertainty)              coefficient   std. error      z      p-value   -------------------------------------------------------   Constant    0.0727286    0.0303053     2.400    0.0164  **   IBO        -0.487763     0.233237     -2.091    0.0365  **   IDE         0.116314     0.505722      0.2300   0.8181   Observations = 49   Degrees of Freedom = 46   Sum of Squared Errors = 0.0374399   Residual Variance = 0.000813911   R-squared = 0.178561