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regstats2

version 1.9.0.0 (77.4 KB) by Oleg Komarov
Regstats enhanced. Robust std.errors; loops on a matrix of responses, 'onlydata' model.

4.7K Downloads

Updated 01 Oct 2011

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[ADDITION_1]
This enhanced version of regstats has implemented several methods to estimate robust standard errors for coefficients:

- HC0: White robust t statistics (Eicker,1963,1967; Huber,1967; White,1980)
- HC1: With dfe correction (Hinkley,1977)
- HC2: White weighted by 1-h (MacKinnon & White,1985)
- HC3: White weighted by (1-h)^2 (Davidson & MacKinnon,1993)
- HC4: White weighted by (1-h)^delta (Cribari & Neto,2004)
- HAC: Newey West t statistics (Newey & West,1987)

Other fields (available from p5v2; visible from p5v5):
- 'empty': if the regression is performed on all NaN series the regstats2 skips the computations and sets to true this field.
- 'rankdef': if after the autoremoval of the NaNs, the design matrix is rank defiecient, regstats2 skips the computations and sets his field to true.

Those fields are meant to easily individuate those series that would otherwise interrupt the looping of the regression.

[ADDITION_2]
This fcn allows to supply a matrix of responses, where each columns is considered as a distinct series, instead of just a vector. The engine will loop through each column returning a set of results for each regression.

[ADDITION_3]
From p5v6 the MODEL argument can also be 'onlydata'. Under this option the DATA is left as it is (no constant or interaction terms are addded).

[ADDITION_4]
From p5v7 QLIKE loss function as in Patton (2011b).

KNOWN ISSUES:
- The GUI is oversized due to the additions. Use the Help to choose the statistics and supply a cellarray with the names of the statistics.

For major details see the help of the fcn
The published M-file contains a direct comparison with the original regstats fcn.

Comments/suggestions/error reports are welcome.

p5v7

Cite As

Oleg Komarov (2021). regstats2 (https://www.mathworks.com/matlabcentral/fileexchange/26169-regstats2), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2009b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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