On stepwise regression
نویسنده
چکیده
Given data y and k covariates x one problem in linear regression is to decide which in any of the covariates to include when regressing y on the x. If k is small it is possible to evaluate each subset of the x. If however k is large then some other procedure must be use. Stepwise regression and the lasso are two such procedures but they both assume a linear model with error term. A different approach is taken here which does not assume a model. A covariate is included if it is better than random noise. This defines a procedure which is simple both conceptually and algorithmically.
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