A novel Bayesian computational approach for bridge-randomized quantile regression in high dimensional models

IF 1.1 4区数学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Statistical Computation and Simulation Pub Date : 2024-05-30 DOI:10.1080/00949655.2024.2361303

Shen Zhang, Mai Dao, Keying Ye, Zifei Han, Min Wang

引用次数: 0

Abstract

A bridge-randomized penalization that employs a prior for the shrinkage parameter, as opposed to the conventional bridge penalization with a fixed penalty, often delivers more superior performance ...

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高维模型中桥随机量化回归的新型贝叶斯计算方法

与采用固定惩罚的传统桥式惩罚相比，采用收缩参数先验的桥式随机惩罚往往能带来更优越的性能......

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Statistical Computation and Simulation 数学-计算机：跨学科应用

CiteScore

2.30

自引率

8.30%

发文量

156

审稿时长

4-8 weeks

期刊介绍： Journal of Statistical Computation and Simulation ( JSCS ) publishes significant and original work in areas of statistics which are related to or dependent upon the computer. Fields covered include computer algorithms related to probability or statistics, studies in statistical inference by means of simulation techniques, and implementation of interactive statistical systems. JSCS does not consider applications of statistics to other fields, except as illustrations of the use of the original statistics presented. Accepted papers should ideally appeal to a wide audience of statisticians and provoke real applications of theoretical constructions.