Premium
Statistical inference for multivariate partially linear regression models
Author(s) -
You Jinhong,
Zhou Yong,
Chen Gemai
Publication year - 2013
Publication title -
canadian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.804
H-Index - 51
eISSN - 1708-945X
pISSN - 0319-5724
DOI - 10.1002/cjs.11169
Subject(s) - estimator , nonparametric statistics , multivariate statistics , statistical inference , statistics , mathematics , asymptotic distribution , nonparametric regression , inference , parametric statistics , statistical hypothesis testing , linear regression , econometrics , linear model , computer science , artificial intelligence
In this paper we study a class of multivariate partially linear regression models. Various estimators for the parametric component and the nonparametric component are constructed and their asymptotic normality established. In particular, we propose an estimator of the contemporaneous correlation among the multiple responses and develop a test for detecting the existence of such contemporaneous correlation without using any nonparametric estimation. The performance of the proposed estimators and test is evaluated through some simulation studies and an analysis of a real data set is used to illustrate the developed methodology. The Canadian Journal of Statistics 41: 1–22; 2013 © 2013 Statistical Society of Canada