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dbd (version 0.0-22)

Discretised Beta Distribution

Description

Tools for working with a new versatile discrete distribution, the db ("discretised Beta") distribution. This package provides density (probability), distribution, inverse distribution (quantile) and random data generation functions for the db family. It provides functions to effect conveniently maximum likelihood estimation of parameters, and a variety of useful plotting functions. It provides goodness of fit tests and functions to calculate the Fisher information, different estimates of the hessian of the log likelihood and Monte Carlo estimation of the covariance matrix of the maximum likelihood parameter estimates. In addition it provides analogous tools for working with the beta-binomial distribution which has been proposed as a competitor to the db distribution.

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Version

Install

install.packages('dbd')

Monthly Downloads

217

Version

0.0-22

License

GPL (>= 2)

Maintainer

Rolf Turner

Last Published

August 19th, 2021

Functions in dbd (0.0-22)

hrsRcePred

Horse race prediction data.
finfo

Fisher information.
aHess

Analytic hessian.
exactMeDb

Exact moment estimates for the db distribution.
dbd-internal

Internal Verdis functions.
gof

Goodness of fit test for db and beta binomial distributions.
expValDb

Expected value of a db distribution.
expValBb

Expected value of a beta binomial distribution.
mcCovMat

Monte Carlo estimation of a covariance matrix.
eow

Set or query the value of the "maxitErrorOrWarn" option.
db

The db (“discretised Beta”) distribution.
makeDbdpars

Create an object of class "Dbdpars".
makeBbdpars

Create an object of class "Bbdpars".
ndata

Retrieve the "ndata" attribute of an "mleDb" object.
plot.mleBb

Plot a maxium likelihood fit to data from a beta binomial distribution.
varBb

Variance of a beta binomial distribution.
nHess

Numerical hessian calculation.
mleDb

Maximum likelihood estimates of db parameters.
varDb

Variance of a db distribution.
vcov.mleDb

Retrieve the covariance matrix from an "mleDb" object.
llPlot

Plot the log likelihood surface for the data.
plotBb

Plot a beta binomial distribution.
plot.mleDb

Plot a maxium likelihood fit to data from a db distribution.
vcov.mleBb

Retrieve the covariance matrix from an "mleBb" object.
plotDb

Plot a db distribution.
mleBb

Maximum likelihood estimation of the parameters of a beta binomial distribution.
logLik

Retrieve the (maximised) log likelihood from an "mleDb" or an "mleBb" object.
visRecog

Visual recognition data.
simulate

Simulate data from a db or beta binomial distribution.