patchGNU Octave - Patches: patch #8584, [octave forge] (statistics)...

 
 

patch #8584: [octave forge] (statistics) stepwisefit selection on partial p values

Submitted by:  Mikael Kurula <alcarola>
Submitted on:  Sun 21 Dec 2014 07:36:44 PM UTC  
 
Category:  Forge : other Priority:  5 - Normal
Status:  None Privacy:  Public
Assigned to:  None Open/Closed:  Open

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Sun 21 Dec 2014 07:36:44 PM UTC, original submission:  

I made some rather trivial modifications to Nir Krakauer's stepwisefit.m in the statistics package, in order to select predictors to consider for inclusion in the models based on partial p values, rather than on correlation with the residual. This is as far as I can understand also suggested in Section 2.9 of Draper & Smith: Applied Regression Analysis, second edition, Wiley 1981.

Drawbacks:
- Computationally probably more intense than correlation
- I am not a statistician, so not so confident that I got it all right

Advantages:
+ Partial p values should be a much more reliable measure of the significance of a predictor than correlation with the residual
+ stepwisefit_p.m seems to perform much better than stepwisefit.m on at least some examples arising from CCD experimental designs

The Octave community is of course free to do what it finds fit with this small development. Thanks to Nir for suggesting that I post the modification here.

Mikael Kurula <alcarola>

 

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Attached Files
file #32698:  stepwisefit_p.m added by alcarola (6KiB - application/octet-stream)

 

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    Follow 3 latest changes.

    Date Changed by Updated Field Previous Value => Replaced by
    2019-03-07 mtmiller Summarystatistics/stepwisefit selection on partial p values => [octave forge] (statistics) stepwisefit selection on partial p values
    2016-07-07 lachlan CategoryNone => Forge : other
    2014-12-21 alcarola Attached File- => Added stepwisefit_p.m, #32698

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