Smoothed Empirical Likelihood Inference for Nonlinear Quantile Regression Models with Missing Response - Open Journal of Applied Sciences

OJAppS > Vol.13 No.6, June 2023

Open Journal of Applied Sciences

Volume 13, Issue 6 (June 2023)

ISSN Print: 2165-3917 ISSN Online: 2165-3925

Google-based Impact Factor: 0.92 Citations h5-index & Ranking

Smoothed Empirical Likelihood Inference for Nonlinear Quantile Regression Models with Missing Response ()

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DOI: 10.4236/ojapps.2023.136074 78 Downloads 292 Views

Author(s)

Honghua Dong, Xiuli Wang^*

Affiliation(s)

School of Mathematics and Statistics, Shandong Normal University, Jinan, China.

ABSTRACT

In this paper, three smoothed empirical log-likelihood ratio functions for the parameters of nonlinear models with missing response are suggested. Under some regular conditions, the corresponding Wilks phenomena are obtained and the confidence regions for the parameter can be constructed easily.

KEYWORDS

Nonlinear Model, Quantile Regression, Smoothed Empirical Likelihood, Missing at Random

Share and Cite:

Dong, H. and Wang, X. (2023) Smoothed Empirical Likelihood Inference for Nonlinear Quantile Regression Models with Missing Response. Open Journal of Applied Sciences, 13, 921-933. doi: 10.4236/ojapps.2023.136074.

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