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CountsEPPM (version 3.1)
Mean and Variance Modeling of Count Data
Description
Modeling under- and over-dispersed count data using extended Poisson process models as in the article Faddy and Smith (2011)
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Version
Version
3.1
3.0
2.1
2.0
1.0
Install
install.packages('CountsEPPM')
Monthly Downloads
223
Version
3.1
License
GPL-2
Maintainer
David Smith
Last Published
January 10th, 2024
Functions in CountsEPPM (3.1)
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coef.CountsEPPM
Extraction of model coefficients for CountsEPPM Objects
summary.CountsEPPM
Method for CountsEPPM object
fitted.CountsEPPM
Extraction of fitted values from CountsEPPM Objects
vcov.CountsEPPM
Variance/Covariance Matrix for Coefficients
print.summaryCountsEPPM
Printing of summaryCountsEPPM Objects
waldtest.CountsEPPM
Wald Test of Nested Models for CountsEPPM Objects
logLik.CountsEPPM
Method for CountsEPPM object
plot.CountsEPPM
Diagnostic Plots for CountsEPPM Objects
Titanic.survivors.case
Titanic survivors data
Model.FaddyJMV.limiting
Function to fit the limiting form of a Faddy distribution for under-dispersed counts.
hatvalues.CountsEPPM
Extraction of hat matrix values from CountsEPPM Objects
residuals.CountsEPPM
Residuals for CountsEPPM Objects
herons.case
Green-backed herons as two groups
herons.group
Green-backed herons as two groups
takeover.bids.case
Takeover bids data.
print.CountsEPPM
Printing of CountsEPPM Objects
predict.CountsEPPM
Prediction Method for CountsEPPM Objects
Model.Faddy
Function for Faddy distribution with log link.
Model.FaddyJMV.general
Function for a general Faddy distribution modeled by means and scale-factors.
LL.gradient
Function used to calculate the first derivatives of the log likelihood with respect to the model parameters.
Faddyprob.limiting
Calculation of vector of probabilities for the limiting form of the Faddy distribution.
CountsEPPM-package
Fitting of EPPM models to count and binary data.
LL.Regression.Counts
Function called by optim to calculate the log likelihood from the probabilities and hence perform the fitting of regression models to the binary data.
Faddyprob.general
Calculation of vector of probabilities for a Faddy distribution.
Luningetal.litters
Number of trials (implantations) in data of Luning, et al. (1966)
EPPMprob
Calculation of vector of probabilities for a extended Poisson process model (EPPM).
Model.Counts
Function for obtaining output from distributional models.
cooks.distance.CountsEPPM
Cook's distance for CountsEPPM Objects
ceriodaphnia.group
Ceriodaphnia data
Williams.litters
Number of trials (implantations) of data of Williams (1996).
LRTruncation
Probabilities for distributions truncated on the left (lower) and/or right (upper).
CountsEPPM
Fitting of EPPM models to count data.