Empirical Likelihood Based Diagnostics for Heteroscedasticity in Semiparametric Varying-Coefficient Partially Linear Models with Missing Responses

LIU Feng · GAO Weiqing · HE Jing · FU Xinwei · KANG Xinmei

1. School of Science, Chongqing University of Technology, Chongqing 401331, China. Email: gwqcq@sina.com
• Online:2021-06-25 Published:2021-03-11

LIU Feng · GAO Weiqing · HE Jing · FU Xinwei · KANG Xinmei. Empirical Likelihood Based Diagnostics for Heteroscedasticity in Semiparametric Varying-Coefficient Partially Linear Models with Missing Responses[J]. Journal of Systems Science and Complexity, 2021, 34(3): 1175-1188.

This paper proposes an empirical likelihood based diagnostic technique for heteroscedasticity for semiparametric varying-coefficient partially linear models with missing responses. Firstly, the authors complement the missing response variables by regression method. Then, the empirical likelihood method is introduced to study the heteroscedasticity of the semiparametric varying-coefficient partially linear models with complete-case data. Finally, the authors obtain the finite sample property by numerical simulation.

 No related articles found!
Viewed
Full text

Abstract