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Semiparametric Analysis of Regression Models for Zero-Inflated Power Series Responses with Missing Covariate
Ehsan Bahrami Samani , Nafeseh Khojasteh Bakht
Abstract:   (685 Views)
In this paper‎, ‎the analysis of count response with many zeros‎, ‎named as zero-inflated data‎, ‎is considered‎. ‎Assumes that responses follow a zero-inflated power series distribution‎. ‎Because of there is missing of the type of random in the covariate‎, ‎some of the data application‎, ‎various methods for estimating of parameters by using the score function with and without missing data for the proposed regression model are presented‎. ‎On the other hand‎, ‎known or unknown selection probability in the missing covariates results in presenting a semi-parametric method for estimating of parameters in the zero-inflated power series regression model‎. ‎To illustrate the proposed method‎, ‎simulation studies and a real example are applied‎. ‎Finally‎, ‎the performance of the semi-parametric method is compared with maximum likelihood‎, ‎complete-case and inverse probability weighted method‎.
Keywords: Zero-Inflated, ‎ ‎Missing Data‎, ‎Score Function‎, ‎Missing at Random‎, ‎Semiparametric Analysis‎, ‎Selection Probability‎.
Full-Text [PDF 5240 kb]   (153 Downloads)    
Type of Study: Applied | Subject: Applied Statistics
Received: 2018/04/9 | Accepted: 2019/04/2
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مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences
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