Semiparametric Analysis of Regression Models for Zero-Inflated Power Series Responses with Missing Covariate
|
Ehsan Bahrami Samani * , Nafeseh Khojasteh Bakht |
|
|
Abstract: (4135 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 206 kb]
(1322 Downloads)
|
Type of Study: Applied |
Subject:
Applied Statistics Received: 2018/04/9 | Accepted: 2019/04/2 | Published: 2020/02/20
|
|
|
|