A Comparison Between Classic Local Least Estimator and Bayesian Method for Estimating Semiparametric Logistic Regression Model

Authors

• Qutaiba N. Nayef Al-Qazaz, Department of Statistics, College of Administration & Economics, University of Baghdad, Republic of Iraq
• Ali Mohammed Ali, Department of Statistics, College of Administration & Economics, University of Baghdad, Republic of Iraq

Abstract

Semi-parametric models analysis is one of the most interesting subjects in recent studies due to give an efficient model estimation. The problem when the response variable has one of two values either 0 ( no response) or one – with response which is called the logistic regression model. We compare two methods Bayesian and . Then the results were compared using MSe criteria. A simulation had been used to study the empirical behavior for the Logistic model , with different sample sizes and variances. The results using represent that the Bayesian method is better than the at small samples sizes.

DOI

10.33095/jeas.v22i88.568

Subject Area

Statistical

First Page

431

Last Page

446

Recommended Citation

Al-Qazaz, Q. N., & Ali, A. M. (2016). A Comparison Between Classic Local Least Estimator and Bayesian Method for Estimating Semiparametric Logistic Regression Model. Journal of Economics and Administrative Sciences, 22(88), 431-446. https://doi.org/10.33095/jeas.v22i88.568