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BinaryEPPM (version 2.3)

Mean and Variance Modeling of Binary Data

Description

Modeling under- and over-dispersed binary data using extended Poisson process models (EPPM) as in the article Faddy and Smith (2012) .

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Version

Install

install.packages('BinaryEPPM')

Monthly Downloads

198

Version

2.3

License

GPL-2

Maintainer

David Smith

Last Published

July 31st, 2019

Functions in BinaryEPPM (2.3)

BBprob

Calculation of vector of probabilities for the beta binomial distribution.

GBprob

Calculation of vector of probabilities for the generalized binomial distribution.

CBprob

Calculation of vector of probabilities for the correlated binomial distribution.

EPPMprob

Calculation of vector of probabilities for a extended Poisson process model (EPPM).

Hiroshima.case

Individual case data of chromosome aberrations in survivors of Hiroshima.

Model.GB

Probabilities for binomial and generalized binomial distributions given p's and b.

Hiroshima.grouped

Data of chromosome aberrations in survivors of Hiroshima grouped into dose ranges and represented as frequency distributions.

Model.BCBinProb

Probabilities for beta and correlated binomial distributions given p's and scale-factors.

KupperHaseman.case

Kupper and Haseman example data

Model.Binary

Function for obtaining output from distributional models.

Model.JMVGB

Probabilities for generalized binomial distributions given p's and scale-factors.

LL.gradient

Function used to calculate the first derivatives of the log likelihood with respect to the model parameters.

cooks.distance.BinaryEPPM

Cook's distance for BinaryEPPM Objects

hatvalues.BinaryEPPM

Extraction of hat matrix values from BinaryEPPM Objects

Luningetal.litters

Number of trials (implantations) in data of Luning, et al., (1966)

doubexp

Double exponential Link Function

negcomplog

Negative complementary log-log Link Function

loglog

Log-log Link Function

LL.Regression.Binary

Function called by optim to calculate the log likelihood from the probabilities and hence perform the fitting of regression models to the binary data.

doubrecip

Double reciprocal Link Function

Titanic.survivors.grouped

Titanic survivors data in frequency distribution form.

predict.BinaryEPPM

Prediction Method for BinaryEPPM Objects

Williams.litters

Number of implantations, data of Williams (1996).

print.BinaryEPPM

Printing of BinaryEPPM Objects

logLik.BinaryEPPM

Extract Log-Likelihood

summary.BinaryEPPM

Summary of BinaryEPPM Objects

vcov.BinaryEPPM

Variance/Covariance Matrix for Coefficients

Yorkshires.litters

The data are of the number of male piglets born in litters of varying sizes for the Yorkshire breed of pigs.

BinaryEPPM-package

BinaryEPPM

coef.BinaryEPPM

Extraction of model coefficients for BinaryEPPM Objects

fitted.BinaryEPPM

Extraction of fitted values from BinaryEPPM Objects

foodstamp.case

Participation in the federal food stamp program.

BinaryEPPM

Fitting of EPPM models to binary data.

Titanic.survivors.case

Individual case data of Titanic survivors

Parkes.litters

The data are of the number of male piglets born in litters of varying sizes for the Parkes breed of pigs.

foodstamp.grouped

Participation in the federal food stamp program as a list not a data frame.

plot.BinaryEPPM

Diagnostic Plots for BinaryEPPM Objects

powerlogit

Power Logit Link Function

ropespores.grouped

Dilution series for the presence of rope spores.

ropespores.case

Dilution series for the presence of rope spores.

print.summaryBinaryEPPM

Printing of summaryBinaryEPPM Objects

residuals.BinaryEPPM

Residuals for BinaryEPPM Objects

waldtest.BinaryEPPM

Wald Test of Nested Models for BinaryEPPM Objects

GasolineYield

Data on gasoline yields.

Berkshires.litters

The data are of the number of male piglets born in litters of varying sizes for the Berkshire breed of pigs.