Results 241 to 250 of about 46,328 (287)

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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Modelling Overdispersion for Complex Survey Data

International Statistical Review, 2001
SummaryThe population characteristics observed by selecting a complex sample from a finite identified population are the result of at least two processes: the process which generates the values attached to the units in the finite population, and the process of selecting the sample of units from the population.
Molina, E.A., Smith, T.M.F., Sugden, R.A.   +2 more
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Overdispersion Tests in Count-Data Analysis

Psychological Reports, 2008
Count data are commonly assumed to have a Poisson distribution, especially when there is no diagnostic procedure for checking this assumption. However, count data rarely fit the restrictive assumptions of the Poisson distribution. The violation of much of such assumptions commonly results in overdispersion, which invalidates the Poisson distribution ...
Jaume, Vives, Josep-Maria, Losilla, Maria-Florencia, Rodrigo, Mariona, Portell   +3 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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Likelihood Analyses of Overdispersed Poisson Models

Biometrics, 1997
Summary: An over-dispersed set of counts of sowbugs from 1946 has been used to illustrate Bayesian methods of fitting, but it is shown that with the priors used the results differ little from those for maximum likelihood.
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