Statistics, Department of

 

The R Journal

Date of this Version

12-2021

Document Type

Article

Citation

The R Journal (December 2021) 13(2); Editor: Dianne Cook

Comments

Copyright 2021, The R Foundation. Open access material. License: CC BY 4.0 International

Abstract

When investigators observe non-random samples from populations, sample selectivity problems may occur. The Heckman selection model is widely used to deal with selectivity problems. Based on the EM algorithm, Zhao et al. (2020) developed three algorithms, namely, ECM, ECM(NR), and ECME(NR), which also have the EM algorithm’s main advantages: stability and ease of implementation. This paper provides the implementation of these three new EM-type algorithms in the package EMSS and illustrates the usage of the package on several simulated and real data examples. The comparison between the maximum likelihood estimation method (MLE) and three new EM-type algorithms in robustness issues is further discussed.

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