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May 2019 Influence measures for the Waring regression model
Luisa Rivas, Manuel Galea
Braz. J. Probab. Stat. 33(2): 402-424 (May 2019). DOI: 10.1214/18-BJPS395

Abstract

In this paper, we present a regression model where the response variable is a count data that follows a Waring distribution. The Waring regression model allows for analysis of phenomena where the Geometric regression model is inadequate, because the probability of success on each trial, $p$, is different for each individual and $p$ has an associated distribution. Estimation is performed by maximum likelihood, through the maximization of the $Q$-function using EM algorithm. Diagnostic measures are calculated for this model. To illustrate the results, an application to real data is presented. Some specific details are given in the Appendix of the paper.

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Luisa Rivas. Manuel Galea. "Influence measures for the Waring regression model." Braz. J. Probab. Stat. 33 (2) 402 - 424, May 2019. https://doi.org/10.1214/18-BJPS395

Information

Received: 1 July 2017; Accepted: 1 February 2018; Published: May 2019
First available in Project Euclid: 4 March 2019

zbMATH: 07057454
MathSciNet: MR3919030
Digital Object Identifier: 10.1214/18-BJPS395

Keywords: Appropriate perturbation , beta-geometric distribution , EM algorithm , generalized Cook’s distance , global and local influence

Rights: Copyright © 2019 Brazilian Statistical Association

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Vol.33 • No. 2 • May 2019
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