Selection of Variables in Regression Models Based on Inflated Distributions

Sumathi , K and Rao, Aruna K (2011) Selection of Variables in Regression Models Based on Inflated Distributions. Pakistan journal of statistics operations research, 7 (2). pp. 381-390. ISSN 1816- 2711

[img] PDF
Restricted to Registered users only

Download (222kB) | Request a copy


Regression models based on zero inflated distributions are often used in exploratory data analysis having excess zeroes. The difficulty faced by many researchers is with regard to the selection of covariates to be included in the model. Following the idea of focused information criterion, observed focused information criterion is proposed for model selection. The motivation for this has its roots in the concept of observed Fisher information. Using this criterion, a forward selection procedure is proposed for selection of variables in regression models based on inflated distributions. The procedure is illustrated using a dataset on decayed missing filled teeth (DMFT) index using the modified observed focused information criterion

Item Type: Article
Uncontrolled Keywords: Regression models, Zero inflated distributions, Focussed information criteria, Observed Fisher information, Forward selection procedure
Subjects: Engineering > MIT Manipal > Mathematics
Depositing User: MIT Library
Date Deposited: 11 Jul 2013 07:57
Last Modified: 11 Jul 2013 07:57

Actions (login required)

View Item View Item