Abstract

We develop the smooth threshold estimating equations to do variable selection for partially linear single- index models with responses missing at random. A new type of imputation estimators are computed based on the smooth threshold estimating equations, and at the same time, the important predictors are selected consistently. The oracle properties of the variable selection procedure and parameter estimations are proved. Some simulation studies are conducted to evaluate and illustrate the proposed methods.

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