Valid Post-Selection Inference for Linear LS Regression
Description
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.