mvord: An R Package for Fitting Multivariate Ordinal Regression Models

被引:44
|
作者
Hirk, Rainer [1 ]
Hornik, Kurt [1 ]
Vana, Laura [1 ]
机构
[1] WU Wirtschaftsuniv Wien, Inst Stat & Math, Dept Finance Accounting & Stat, A-1020 Vienna, Austria
来源
JOURNAL OF STATISTICAL SOFTWARE | 2020年 / 93卷 / 04期
关键词
composite likelihood estimation; correlated ordinal data; multivariate ordinal logit regression model; multivariate ordinal probit regression model; R; LIKELIHOOD INFERENCE; DEBT;
D O I
10.18637/jss.v093.i04
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The R package mvord implements composite likelihood estimation in the class of multivariate ordinal regression models with a multivariate probit and a multivariate logit link. A flexible modeling framework for multiple ordinal measurements on the same subject is set up, which takes into consideration the dependence among the multiple observations by employing different error structures. Heterogeneity in the error structure across the subjects can be accounted for by the package, which allows for covariate dependent error structures. In addition, different regression coefficients and threshold parameters for each response are supported. If a reduction of the parameter space is desired, constraints on the threshold as well as on the regression coefficients can be specified by the user. The proposed multivariate framework is illustrated by means of a credit risk application.
引用
收藏
页码:1 / 41
页数:41
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