Results 241 to 250 of about 45,763 (274)

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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Phylogenetic Overdispersion in Floridian Oak Communities

The American Naturalist, 2004
Closely related species that occur together in communities and experience similar environmental conditions are likely to share phenotypic traits because of the process of environmental filtering. At the same time, species that are too similar are unlikely to co-occur because of competitive exclusion.
J, Cavender-Bares, D D, Ackerly, D A, Baum, F A, Bazzaz   +3 more
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A note on overdispersed exponential families

Biometrika, 1990
Abstract : The issue of creating overdispersion in a given one parameter one dimensional exponential family, by extending it to a two parameter exponential family with the same support, is considered. An easily verifiable sufficient condition for this is derived.
A. E. Gelfand, S. R. Dalal
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Overdispersion and Poisson Regression

Journal of Quantitative Criminology, 2008
This article discusses the use of regression models for count data. A claim is often made in criminology applications that the negative binomial distribution is the conditional distribution of choice when for a count response variable there is evidence of overdispersion.
Richard Berk, John M. MacDonald
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Overdispersion In Marine Fish Parasites

Journal of Parasitology, 2012
A modification of Taylor's Power law was used to compare the degree of overdispersion in frequency distributions from 38 datasets of marine parasites, data that had originally been collected for fish stock discrimination. The results strongly indicate that the overriding factor contributing to overdispersion in these helminths and crustaceans is the ...
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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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Overdispersed generalized linear models

Journal of Statistical Planning and Inference, 1997
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Dey, Dipak K., Gelfand, Alan E., Peng, Fengchun   +2 more
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Overdispersed Logistic Regression Model

2015
When binary data are obtained through simple random sampling, the covariance for the responses follows the binomial model (two possible outcomes from independent observations with constant probability). However, when the data are obtained under other circumstances, the covariances of the responses differ substantially from the binomial case.
Jeffrey R. Wilson, Kent A. Lorenz
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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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Modelling overdispersed Poisson data

2022
This thesis was scanned from the print manuscript for digital preservation and is copyright the author. Researchers can access this thesis by asking their local university, institution or public library to make a request on their behalf. Monash staff and postgraduate students can use the link in the References field.
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