Bayesian skew-probit regression for binary response data

被引:14
作者
Bazan, Jorge L. [1 ]
Romeo, Jose S. [2 ]
Rodrigues, Josemar [1 ]
机构
[1] Univ Sao Paulo, Inst Ciencias Matemat & Comp, BR-13560970 Sao Carlos, SP, Brazil
[2] Univ Santiago Chile, Dept Matemat & Ciencia Comp, Santiago, Chile
基金
巴西圣保罗研究基金会;
关键词
Skew-probit links; binary regression; Bayesian estimation; power normal distribution; reciprocal power normal distribution; MODEL;
D O I
10.1214/13-BJPS218
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Since many authors have emphasized the need of asymmetric link functions to fit binary regression models, we propose in this work two new skew-probit link functions for the binary response variables. These link functions will be named power probit and reciprocal power probit due to the relation between them including the probit link as a special case. Also, the probit regressions are special cases of the models considered in this work. A Bayesian inference approach using MCMC is developed for real data suggesting that the link functions proposed here are more appropriate than other link functions used in the literature. In addition, simulation study show that the use of probit model will lead to biased estimate of the regression coefficient.
引用
收藏
页码:467 / 482
页数:16
相关论文
共 50 条
  • [21] Enhanced decision support in credit scoring using Bayesian binary quantile regression
    Migueis, V. L.
    Benoit, D. F.
    Van den Poel, D.
    JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, 2013, 64 (09) : 1374 - 1383
  • [22] Bayesian Analysis of Aberrant Response and Response Time Data
    Zhang, Zhaoyuan
    Zhang, Jiwei
    Lu, Jing
    FRONTIERS IN PSYCHOLOGY, 2022, 13
  • [23] Bayesian Tensor Response Regression with an Application to Brain Activation Studies
    Guhaniyogi, Rajarshi
    Spencer, Daniel
    BAYESIAN ANALYSIS, 2021, 16 (04): : 1221 - 1249
  • [24] A Heterogeneous Bayesian Regression Model for Cross-sectional Data Involving a Single Observation per Response Unit
    Fong D.K.H.
    Ebbes P.
    DeSarbo W.S.
    Psychometrika, 2012, 77 (2) : 293 - 314
  • [25] Bayesian Semiparametric Regression Analysis of Multivariate Panel Count Data
    Wang, Chunling
    Lin, Xiaoyan
    STATS, 2022, 5 (02): : 477 - 493
  • [26] USE BAYESIAN ADAPTIVE LASSO FOR TOBIT REGRESSION WITH REAL DATA
    AL-Sabbah, Shrook A. S.
    Raheem, Saif Hosam
    INTERNATIONAL JOURNAL OF AGRICULTURAL AND STATISTICAL SCIENCES, 2021, 17 : 2169 - 2173
  • [27] A Bayesian approach for semiparametric regression analysis of panel count data
    Wang, Jianhong
    Lin, Xiaoyan
    LIFETIME DATA ANALYSIS, 2020, 26 (02) : 402 - 420
  • [28] Bayesian Quantile Regression for Longitudinal Studies with Nonignorable Missing Data
    Yuan, Ying
    Yin, Guosheng
    BIOMETRICS, 2010, 66 (01) : 105 - 114
  • [29] Bayesian Nonlinear Quantile Regression Approach for Longitudinal Ordinal Data
    Yang, Hang
    Chen, Zhuojian
    Zhang, Weiping
    COMMUNICATIONS IN MATHEMATICS AND STATISTICS, 2019, 7 (02) : 123 - 140
  • [30] A HETEROGENEOUS BAYESIAN REGRESSION MODEL FOR CROSS-SECTIONAL DATA INVOLVING A SINGLE OBSERVATION PER RESPONSE UNIT
    Fong, Duncan K. H.
    Ebbes, Peter
    DeSarbo, Wayne S.
    PSYCHOMETRIKA, 2012, 77 (02) : 293 - 314