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- Title
Smooth empirical likelihood of quantile regression with missing data and auxiliary information.
- Authors
JI Xiaoxiao; ZHANG Chengyi; LUO Shuanghua
- Abstract
To research the statistical inference problem of linear quantile regression model with missing response data and auxiliary information, by using the method of smooth empirical likelihood, based on the smooth empirical likelihood method, the parameter estimation of the linear quantile regression model is proposed. The smooth empirical logarithmic likelihood ratio of the quantile regression model is defined, and under certain conditions, the constructed smooth empirical logarithmic likelihood ratio is proved to obey the chi-square distribution, and then the confidence interval is constructed according to the likelihood ratio. The asymptotic normality of the obtained quantile smooth empirical likelihood estimation is established and the validity of the obtained estimation is illustrated by numerical experiments.
- Subjects
QUANTILE regression; INFERENTIAL statistics; CHI-square distribution; ASYMPTOTIC normality; REGRESSION analysis; PARAMETER estimation
- Publication
Basic Sciences Journal of Textile Universities / Fangzhi Gaoxiao Jichu Kexue Xuebao, 2020, Vol 33, Issue 2, p70
- ISSN
1006-8341
- Publication type
Article
- DOI
10.13338/j.issn.1006-8341.2020.02.012