Variational Bayesian Inference for Quantile Regression Models with Nonignorable Missing Data

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...

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發表在:	Mathematics
Main Authors:	Xiaoning Li, Mulati Tuerde, Xijian Hu
格式:	Article
語言:	英语
出版:	MDPI AG 2023-09-01
主題:	lasso regularization nonignorable missing data quantile regression variational Bayesian inference
在線閱讀:	https://www.mdpi.com/2227-7390/11/18/3926