A hyper-Poisson regression model for overdispersed and underdispersed count data

被引：51
|
作者：
Saez-Castillo, A. J. [1 ]
Conde-Sanchez, A. [1 ]
机构：
[1] Univ Jaen, Dept Stat & Operat Res, Linares 23700, Jaen, Spain
来源：
COMPUTATIONAL STATISTICS & DATA ANALYSIS | 2013年 / 61卷
关键词：
Regression model; Count data; Hyper-Poisson; Overdispersion; Underdispersion; SERIES;
D O I：
10.1016/j.csda.2012.12.009
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
The Poisson regression model is the most common framework for modeling count data, but it is constrained by its equidispersion assumption. The hyper-Poisson regression model described in this paper generalizes it and allows for over- and under-dispersion, although, unlike other models with the same property, it introduces the regressors in the equation of the mean. Additionally, regressors may also be introduced in the equation of the dispersion parameter, in such a way that it is possible to fit data that present overdispersion and underdispersion in different levels of the observations. Two applications illustrate that the model can provide more accurate fits than those provided by alternative usual models. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码：148 / 157
页数：10
相关论文
共 50 条
  • [31] Estimation and influence diagnostics for zero-inflated hyper-Poisson regression model: full Bayesian analysis
    Cancho, Vicente G.
    Bao Yiqi
    Fiorucci, Jose A.
    Barriga, Gladys D. C.
    Dey, Dipak K.
    COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2018, 47 (11) : 2741 - 2759
  • [32] A generalized model for overdispersed count data
    Okamura, Hiroshi
    Punt, Andre E.
    Amano, Tatsuya
    POPULATION ECOLOGY, 2012, 54 (03) : 467 - 474
  • [33] A New Regression Model for the Analysis of Overdispersed and Zero-Modified Count Data
    Bertoli, Wesley
    Conceicao, Katiane S.
    Andrade, Marinho G.
    Louzada, Francisco
    ENTROPY, 2021, 23 (06)
  • [34] Systematic errors in the maximum-likelihood regression of Poisson count data: introducing the overdispersed χ2 distribution
    Bonamente, Massimiliano
    MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, 2023, 522 (02) : 1987 - 2001
  • [35] A Time-Series Model for Underdispersed or Overdispersed Counts
    MacDonald, Iain L.
    Bhamani, Feroz
    AMERICAN STATISTICIAN, 2020, 74 (04): : 317 - 328
  • [36] COMPUTER PROOF OF THE HYPER-POISSON NONINFINITE DIVISIBILITY
    DANIEL, EJ
    KATTI, SK
    AMERICAN STATISTICAL ASSOCIATION 1988 PROCEEDINGS OF THE STATISTICAL COMPUTING SECTION, 1988, : 280 - 283
  • [37] A Bayesian generalized random regression model for estimating heritability using overdispersed count data
    Mair, Colette
    Stear, Michael
    Johnson, Paul
    Denwood, Matthew
    de Cisneros, Joaquin Prada Jimenez
    Stefan, Thorsten
    Matthews, Louise
    GENETICS SELECTION EVOLUTION, 2015, 47
  • [38] Discrete Extension of Poisson Distribution for Overdispersed Count Data: Theory and Applications
    Eliwa, Mohamed S.
    Ahsan-ul-Haq, Muhammad
    Almohaimeed, Amani
    Al-Bossly, Afrah
    El-Morshedy, Mahmoud
    JOURNAL OF MATHEMATICS, 2023, 2023
  • [39] Dirichlet negative multinomial regression for overdispersed correlated count data
    Farewell, Daniel M.
    Farewell, Vernon T.
    BIOSTATISTICS, 2013, 14 (02) : 395 - 404
  • [40] A Bayesian generalized random regression model for estimating heritability using overdispersed count data
    Colette Mair
    Michael Stear
    Paul Johnson
    Matthew Denwood
    Joaquin Prada Jimenez de Cisneros
    Thorsten Stefan
    Louise Matthews
    Genetics Selection Evolution, 47
12345