Results 221 to 230 of about 20,066 (266)

Spatial scan statistics with overdispersion

Statistics in Medicine, 2011
The spatial scan statistic has been widely used in spatial disease surveillance and spatial cluster detection for more than a decade. However, overdispersion often presents in real‐world data, causing not only violation of the Poisson assumption but also excessive type I errors or false alarms.
Tonglin, Zhang, Zuoyi, Zhang, Ge, Lin
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Overdispersion

1999
Abstract Categorical data are produced when the response is an indicator of which of a number of events has occurred. However, these will be repeated measurements only if repeated events are observed on the same units (Section 1.2). When no explanatory variables, not even time, distinguish such responses on a unit, the events can be ...
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A note on the overdispersed Poisson family

Insurance: Mathematics and Economics, 2002
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Approaches to Modelling Overdispersion in the Analysis of Migration [PDF]

Environment and Planning A: Economy and Space, 1993
In this paper the modelling of overdispersion in generalised Poisson and multinomial models of migration flows and rates is considered, and its importance within the wider question of substantive model specification is shown. It is argued that substantive specification and the modelling of overdispersion are closely interrelated.
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A Note on a Test for Poisson Overdispersion

Biometrika, 1994
SUMMARY This note discusses an error occurring in a test for Poisson overdispersion suggested by Tiago de Oliveira (1965). The limiting null distribution of the suggested statistic is neither pivotal nor is it standard normal. The error lies in the computation of the asymptotic standard error of the overdispersion estimate, for which a corrected ...
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Testing Overdispersion in CUBE Models

Communications in Statistics - Simulation and Computation, 2014
A practical problem with large-scale survey data is the possible presence of overdispersion. It occurs when the data display more variability than is predicted by the variance–mean relationship. This article describes a probability distribution generated by a mixture of discrete random variables to capture uncertainty, feeling, and overdispersion ...
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Hypothesis Testing for Proportions with Overdispersion

Biometrics, 1986
The properties of likelihood ratio tests and simpler t-tests are investigated by simulation under an assumed beta-binomial model for parameter values typically found in toxicological studies. It is found that likelihood ratio methods are at least as powerful as the simpler approaches and in certain situations can be significantly more powerful.
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On modelling overdispersion of counts

Statistica Neerlandica, 1999
For counts it often occurs that the observed variance exceeds the nominal variance of the claimed binomial, multinomial or Poisson distributions. We study how models can be extended to cope with this phenomenon: a survey of literature is given. We focus on modelling, not on estimation or testing statistical hypotheses.
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Modeling Overdispersion in R

2015
The book Overdispersion Models in SAS by Morel and Neerchal (2012) discusses statistical analysis of categorical and count data which exhibit overdispersion, with a focus on computational procedures using SAS. This document retraces some of the ground covered in the book, which we abbreviate throughout as OMSAS, with the objective of carrying out ...
Raim, Andrew M., Neerchal, Nagaraj K., Morel, Jorge G.   +2 more
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Overdispersion in nuclear statistics

Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 1999
Abstract The modern statistical distribution theory is applied to the development of the overdispersion theory in ionizing-radiation statistics for the first time. The physical nuclear system is treated as a sequence of binomial processes, each depending on a characteristic probability, such as probability of decay, detection, etc.
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