Function fit_t_pl: same codes, very different results on 32 or 64-bit R about panda HOT 3 CLOSED

Hi Silvia,

It's hard to track the problem without a reproducible example. Small differences are expected between 32 and 64 bits versions since they’re not using the same math libraries and rounding. When I’m running the example code from ?GIC.fit_pl.rpanda on a Windows machine with both 32 and 64 bits versions (R-3.6.3) installed I can indeed find very small differences in parameter search. But the results are almost the same:

sessionInfo()
R version 3.6.3 (2020-02-29)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 18362)
//
// with the example code from ?GIC.fit_pl.rpanda
//
GIC(fit1); GIC(fit2)

-- Generalized Information Criterion --

GIC: 7190.805 | Log-likelihood -3432.328

-- Generalized Information Criterion --

GIC: 7192.806 | Log-likelihood -3432.329

sessionInfo()
R version 3.6.3 (2020-02-29)
Platform: i386-w64-mingw32/i386 (32-bit)
Running under: Windows 10 x64 (build 18362)
GIC(fit1); GIC(fit2)

-- Generalized Information Criterion --

GIC: 7190.805 | Log-likelihood -3432.328

-- Generalized Information Criterion --

GIC: 7192.77 | Log-likelihood -3432.303

In your situation, it seems that there’s almost no need for regularization (the “gamma” parameter is very low). It’s possible that this led to numerical underflow affecting the program. If this is the cause, one solution might be to set the “tol” parameter to some small values (e.g. tol=1e-8; see ?fit_t_pl). You can also switch to ML or try another penalty. Sometime working on a scaled tree can also helps.

HTH,

Regards

Julien

from panda.

Dear Julien,

thank you very much for your response! I followed your suggestion of changing the value for the regularization parameter, and it solves the problem of the inconsistency between the two versions of R, which now give the same results. However, it also strongly affects the estimation of the models parameters and the model’s comparison with the GIC. So, after trying out, I think I will stick with the 64-bit, whose outcomes looks more reliable then the 32-bit.

Thank you very much for your help!

Regards,
Silvia

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from panda.