Brazilian Journal of Probability and Statistics

Influence measures for the Waring regression model

Luisa Rivas and Manuel Galea

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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.

Article information

Braz. J. Probab. Stat., Volume 33, Number 2 (2019), 402-424.

Received: July 2017
Accepted: February 2018
First available in Project Euclid: 4 March 2019

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Mathematical Reviews number (MathSciNet)

Zentralblatt MATH identifier

EM algorithm beta-geometric distribution generalized Cook’s distance appropriate perturbation global and local influence


Rivas, Luisa; Galea, Manuel. Influence measures for the Waring regression model. Braz. J. Probab. Stat. 33 (2019), no. 2, 402--424. doi:10.1214/18-BJPS395.

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