Staff Members - Benha University
Bayesian Semi-Parametric Logistic Regression Model with Application to Credit Scoring Data
JDS • 2016
Publication Information
Authors
Haitham M. Yousof,
Ahmed M. Gad
Keywords
Generalized partial linear model, semi-parametric logistic
regression model, parametric logistic regression model, Profile likelihood
method, Bayesian estimation, Square error loss function.
Journal
JDS
Publisher
Not Available
Volume
Not Available
Issue
Not Available
Pages
Not Available
publication.type
International
Paper Link
Not Available
Supplementary Materials
Not Available
Abstract
In this article a new Bayesian regression model, called the Bayesian
semi-parametric logistic regression model, is introduced. This model generalizes
the semi-parametric logistic regression model (SLoRM) and improves its
estimations. This paper considers Bayesian and non-Bayesian estimation and
inference for the parametric and semi-parametric logistic regression model with
application to credit scoring data under the square error loss function. This paper
introduces a new algorithm for estimating the SLoRM parameters using Bayesian
theorem in more detail. Finally, the parametric logistic regression model
(PLoRM), the SLoRM and the Bayesian SLoRM are used and compared using a
real data set.
semi-parametric logistic regression model, is introduced. This model generalizes
the semi-parametric logistic regression model (SLoRM) and improves its
estimations. This paper considers Bayesian and non-Bayesian estimation and
inference for the parametric and semi-parametric logistic regression model with
application to credit scoring data under the square error loss function. This paper
introduces a new algorithm for estimating the SLoRM parameters using Bayesian
theorem in more detail. Finally, the parametric logistic regression model
(PLoRM), the SLoRM and the Bayesian SLoRM are used and compared using a
real data set.