Results 171 to 180 of about 1,308 (195)

Integer-valued autoregressive models for counts showing underdispersion

Journal of Applied Statistics, 2013
The Poisson distribution is a simple and popular model for count-data random variables, but it suffers from the equidispersion requirement, which is often not met in practice. While models for overdispersed counts have been discussed intensively in the literature, the opposite phenomenon, underdispersion, has received only little attention, especially ...
Christian H Weis
exaly   +2 more sources

An empirical model for underdispersed count data

Statistical Modelling, 2004
We present a novel distribution for modelling count data that are underdispersed relative to the Poisson distribution. The distribution is a form of weighted Poisson distribution and is shown to have advantages over other weighted Poisson distributions that have been proposed to model underdispersion.
Ridout, Martin S., Besbeas, Panagiotis
openaire   +2 more sources

Pseudo R-squared measures for Poisson regression models with over- or underdispersion

Computational Statistics and Data Analysis, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Harald Heinzl, Martina Mittlböck
exaly   +3 more sources

Likelihood‐Based Modeling and Analysis of Data Underdispersed Relative to the Poisson Distribution

Biometrics, 2001
Summary. By using a generalization of the Poisson process, distributions can be constructed that show appropriate amounts of underdispersion relative to the Poisson distribution that may be apparent from observed data. These are then used to examine the differences between the distributions of numbers of fetal implants in mice corresponding to ...
Faddy, M. J., Bosch, R. J.
openaire   +3 more sources

A Time-Series Model for Underdispersed or Overdispersed Counts

The American Statistician, 2018
It is common for time series of unbounded counts (that is, nonnegative integers) to display overdispersion relative to the Poisson.
Iain L. MacDonald, Feroz Bhamani
openaire   +2 more sources

Flexible models for non-equidispersed count data: comparative performance of parametric models to deal with underdispersion

AStA Advances in Statistical Analysis, 2022
Count data as response variables are commonly modeled using Poisson regression models, which require equidispersion, i.e., equal mean and variance. However, this relationship does not always occur, and the variance may be higher or lower than the mean ...
Douglas Toledo, Camargo Afm
exaly   +2 more sources

Overdispersed and underdispersed Poisson generalizations

Journal of Statistical Planning and Inference, 2005
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
del Castillo, Joan, Pérez-Casany, Marta
openaire   +2 more sources

hyper-Poisson Model for Overdispersed and Underdispersed Count Data

Proceedings of The International Conference on Data Science and Official Statistics, 2023
The Poisson model is commonly used for modelling count data. However, it has a limitation, namely the equality between the mean and variance (equidispersion) of the data to be modeled. Unfortunately, overdispersion (variance greater than the mean) and underdispersion (variance smaller than the mean) are more often to be found in real cases.
Venda Damianus Situmorang, Siti Nurrohmah, Ida Fithriani   +2 more
openaire   +1 more source

Flexible INAR(1) models for equidispersed, underdispersed or overdispersed counts

Journal of the Korean Statistical Society, 2022
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kang, Yao, Wang, Dehui, Lu, Feilong, Wang, Shuhui   +3 more
openaire   +2 more sources

The AGU-F distribution : Properties and applications on over and underdispersed data

Journal of Statistics and Management Systems, 2021
In this paper, we introduced a one-parameter lifetime distribution called the Agu-F distribution (Agu-F-D) and explored some of its useful statistical properties. The numerical applications of the Agu-F-D was examined using over and under dispersed, low and high kurtosis, positively, and negatively skewed three lifetime data sets.
Paschal, Iwundu Mary, Agu, Friday Ikechukwu, Eghwerido, Joseph Thomas   +2 more
openaire   +2 more sources