Empirical Likelihood for Partially Linear Single-Index Models under Negatively Associated Errors

Empirical Likelihood for Partially Linear Single-Index Models under Negatively Associated Errors

In this paper, the authors consider the application of the blockwise empirical likelihood method to the partially linear single-index model when the errors are negatively associated, which often exist in sequentially collected economic data. Thereafter, the blockwise empirical likelihood ratio stati...

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Main Authors: Xin Qi, ZhuoXi Yu
Format: Article
Language:English
Published: Hindawi Limited 2021-01-01
Series:Journal of Mathematics
Online Access:http://dx.doi.org/10.1155/2021/6628716
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spelling doaj-e5f2ba2f503e4799a61f2f9bdc00cc872021-04-05T00:01:43ZengHindawi LimitedJournal of Mathematics2314-47852021-01-01202110.1155/2021/6628716Empirical Likelihood for Partially Linear Single-Index Models under Negatively Associated ErrorsXin Qi0ZhuoXi Yu1Guangdong Polytechnic of Science and TechnologySchool of EconomicsIn this paper, the authors consider the application of the blockwise empirical likelihood method to the partially linear single-index model when the errors are negatively associated, which often exist in sequentially collected economic data. Thereafter, the blockwise empirical likelihood ratio statistic for the parameters of interest is proved to be asymptotically chi-squared. Hence, it can be directly used to construct confidence regions for the parameters of interest. A few simulation experiments are used to illustrate our proposed method.http://dx.doi.org/10.1155/2021/6628716
collection DOAJ
language English
format Article
sources DOAJ
author Xin Qi
ZhuoXi Yu
spellingShingle Xin Qi
ZhuoXi Yu
Empirical Likelihood for Partially Linear Single-Index Models under Negatively Associated Errors
Journal of Mathematics
author_facet Xin Qi
ZhuoXi Yu
author_sort Xin Qi
title Empirical Likelihood for Partially Linear Single-Index Models under Negatively Associated Errors
title_short Empirical Likelihood for Partially Linear Single-Index Models under Negatively Associated Errors
title_full Empirical Likelihood for Partially Linear Single-Index Models under Negatively Associated Errors
title_fullStr Empirical Likelihood for Partially Linear Single-Index Models under Negatively Associated Errors
title_full_unstemmed Empirical Likelihood for Partially Linear Single-Index Models under Negatively Associated Errors
title_sort empirical likelihood for partially linear single-index models under negatively associated errors
publisher Hindawi Limited
series Journal of Mathematics
issn 2314-4785
publishDate 2021-01-01
description In this paper, the authors consider the application of the blockwise empirical likelihood method to the partially linear single-index model when the errors are negatively associated, which often exist in sequentially collected economic data. Thereafter, the blockwise empirical likelihood ratio statistic for the parameters of interest is proved to be asymptotically chi-squared. Hence, it can be directly used to construct confidence regions for the parameters of interest. A few simulation experiments are used to illustrate our proposed method.
url http://dx.doi.org/10.1155/2021/6628716
work_keys_str_mv AT xinqi empiricallikelihoodforpartiallylinearsingleindexmodelsundernegativelyassociatederrors
AT zhuoxiyu empiricallikelihoodforpartiallylinearsingleindexmodelsundernegativelyassociatederrors
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