Valid Post-Selection Inference for Linear LS Regression

In linear LS regression, calculate for a given design matrix the multiplier K of coefficient standard errors such that the confidence intervals [b - K*SE(b), b + K*SE(b)] have a guaranteed coverage probability for all coefficient estimates b in any submodels after performing arbitrary model selection.


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1.1 by Wan Zhang, a year ago

Browse source code at

Authors: Andreas Buja [aut] , Kai Zhang [aut] , Wan Zhang [cre]

Documentation:   PDF Manual  

GPL-3 license

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