Variational Bayesian Inference for Quantile Regression Models with Nonignorable Missing Data

• Published in: Mathematics (Basel) Vol. 11; no. 18; p. 3926
• Main Authors: Li, Xiaoning, Tuerde, Mulati, Hu, Xijian
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.09.2023
• Subjects: Adultery; Algorithms; Approximation; Bayesian analysis; Bayesian statistical decision theory; Data analysis; Data collection; Electronic data processing; Feature selection; Human error; lasso regularization; Mathematics; Methods; Missing data; nonignorable missing data; Optimization techniques; Parameter estimation; Quantile regression; Regression analysis; Regression models; Statistical inference; Variables; variational Bayesian inference; China

Quantile regression models are remarkable structures for conducting regression analyses when the data are subject to missingness. Missing values occur because of various factors like missing completely at random, missing at random, or missing not at random. All these may result from system malfuncti...