Minimum phi-divergence estimators for multinomial logistic regression with complex sample design |
| |
Authors: | Elena Castilla Nirian Martín Leandro Pardo |
| |
Affiliation: | 1.Department of Statistics and Operations Research,Complutense University of Madrid,Madrid,Spain |
| |
Abstract: | This article develops the theoretical framework needed to study the multinomial regression model for complex sample design with pseudo-minimum phi-divergence estimators. The numerical example and the simulation study propose new estimators for the parameter of the logistic regression with overdispersed multinomial distributions for the response variables, the pseudo-minimum Cressie–Read divergence estimators, as well as new estimators for the intra-cluster correlation coefficient. The simulation study shows that the Binder’s method for the intra-cluster correlation coefficient exhibits an excellent performance when the pseudo-minimum Cressie–Read divergence estimator, with (lambda =frac{2}{3}), is plugged. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|