Fit Probability Models to Forensic Survey Data

Documentation for package ‘fitPS’ version 1.1.4

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-- A --

add	Add data to a psData object
as.data.frame.psData	Converts an object of class 'psData' to a 'data.frame'

-- B --

bootCI	Legacy bootstrap confidence intervals or regions
bootCI.default	Legacy bootstrap confidence intervals or regions
bootCI.psData	Legacy bootstrap confidence intervals or regions
bootCI.psFit	Legacy bootstrap confidence intervals or regions
bootstrapFit	Compute a bootstrap distribution for a fitted fitPS model
bootstrapFit.psFit	Compute a bootstrap distribution for a fitted fitPS model
bootstrapProbs	Extract bootstrap probability summaries
bootstrapProbs.psBootstrap	Extract bootstrap probability summaries
bootstrapProbs.psFit	Extract bootstrap probability summaries

-- C --

comp.survs	Compare two surveys on the basis of their shape parameters
compare.surveys	Compare two surveys on the basis of their shape parameters
compareSurveys	Compare two surveys on the basis of their shape parameters
compareSurveys.default	Compare two surveys on the basis of their shape parameters
compareSurveys.psData	Compare two surveys on the basis of their shape parameters
compareSurveys.psFit	Compare two surveys on the basis of their shape parameters
compareSurveysLRT	Compare two or more surveys on the basis of their shape parameters using a Likelihood Ratio Test
confint.psFit	S3 confint method for objects of class psFit
createPSData	Create a survey data set manually
credInt	Bayesian credible intervals or regions
credint	Bayesian credible intervals or regions

-- D --

deviance.psFit	Extract deviance from a fitted fitPS model
DIC	Compute the deviance information criterion for a Bayesian fitPS model

-- F --

fit	Fit a fitPS model
fitDist	Fit a Zeta Distribution to Forensic Data
fitdist	Fit a Zeta Distribution to Forensic Data
fitLogdist	Fit a logarithmic distribution to forensic data
fitlogDist	Fit a logarithmic distribution to forensic data
fitlogdist	Fit a logarithmic distribution to forensic data
fitted.psFit	S3 fitted method for an object of class 'psFit'
fitted.psPosterior	Extract posterior mean probabilities
fitZIDist	Fit a Zero-Inflated Zeta Distribution to Forensic Data
fitZIdist	Fit a Zero-Inflated Zeta Distribution to Forensic Data
fitzidist	Fit a Zero-Inflated Zeta Distribution to Forensic Data

-- L --

logarithmicModel	Construct built-in fitPS model descriptors
logLik.psFit	Extract the maximised log-likelihood from a fitPS model fit

-- M --

makeData	Create a survey data set manually
makePrior	Define a prior density
makePSData	Create a survey data set manually
mean.psData	An S3 method for computing the mean of clothing survey for the number of groups or size of groups
modelBayesControl	Return Bayesian fitting controls supplied by a model
modelBayesControl.logarithmicModel	Return Bayesian fitting controls supplied by a model
modelBayesControl.psModel	Return Bayesian fitting controls supplied by a model
modelBayesControl.zetaModel	Return Bayesian fitting controls supplied by a model
modelBayesControl.zizModel	Return Bayesian fitting controls supplied by a model
modelFromUnconstrained	Transform unconstrained coordinates to natural model parameters
modelFromUnconstrained.logarithmicModel	Transform unconstrained coordinates to natural model parameters
modelFromUnconstrained.psModel	Transform unconstrained coordinates to natural model parameters
modelFromUnconstrained.zetaModel	Transform unconstrained coordinates to natural model parameters
modelFromUnconstrained.zizModel	Transform unconstrained coordinates to natural model parameters
modelLogJacobian	Evaluate the log-Jacobian for the unconstrained parameter transformation
modelLogJacobian.logarithmicModel	Evaluate the log-Jacobian for the unconstrained parameter transformation
modelLogJacobian.psModel	Evaluate the log-Jacobian for the unconstrained parameter transformation
modelLogJacobian.zetaModel	Evaluate the log-Jacobian for the unconstrained parameter transformation
modelLogJacobian.zizModel	Evaluate the log-Jacobian for the unconstrained parameter transformation
modelLogLikelihood	Evaluate a model log likelihood through the shared model protocol.
modelLogPrior	Evaluate a model prior on the natural parameter scale
modelLogPrior.logarithmicModel	Evaluate a model prior on the natural parameter scale
modelLogPrior.psModel	Evaluate a model prior on the natural parameter scale
modelLogPrior.zetaModel	Evaluate a model prior on the natural parameter scale
modelLogPrior.zizModel	Evaluate a model prior on the natural parameter scale
modelMleControl	Return generic maximum-likelihood controls for a model
modelMleControl.psModel	Return generic maximum-likelihood controls for a model
modelObservationData	Convert fitPS data to the observation support required by a model.
modelParameterNames	Return the natural parameter names declared by a fitPS model.
modelProbabilities	Evaluate fitted P/S probabilities through a model descriptor.
modelToUnconstrained	Transform natural model parameters to unconstrained coordinates
modelToUnconstrained.logarithmicModel	Transform natural model parameters to unconstrained coordinates
modelToUnconstrained.psModel	Transform natural model parameters to unconstrained coordinates
modelToUnconstrained.zetaModel	Transform natural model parameters to unconstrained coordinates
modelToUnconstrained.zizModel	Transform natural model parameters to unconstrained coordinates

-- P --

plot.psBootstrap	Plot bootstrap probability summaries
plot.psFit	S3 plot method for an object of class 'psFit'
plot.psPosterior	Plot posterior probability summaries
plotPosterior	Plot a posterior density for a fitted power-series model
plotUncertainty	Plot parameter uncertainty for a fitPS inferential result
plotUncertainty.psBayesianBootstrap	Plot parameter uncertainty for a fitPS inferential result
plotUncertainty.psBootstrap	Plot parameter uncertainty for a fitPS inferential result
plotUncertainty.psFit	Plot parameter uncertainty for a fitPS inferential result
posteriorInflation	Posterior probability of practically negligible inflation
posteriorInflation.psFit	Posterior probability of practically negligible inflation
posteriorInflation.psPosterior	Posterior probability of practically negligible inflation
posteriorProbs	Extract posterior probability summaries
posteriorProbs.psFit	Extract posterior probability summaries
posteriorProbs.psPosterior	Extract posterior probability summaries
predict.psFit	S3 predict method for an object of class 'psFit'
print.psBayesianBootstrap	Print a fitPS Bayesian Bootstrap object
print.psBootstrap	Print a fitPS bootstrap object
print.psData	S3 print method for an object of class 'psData'
print.psFit	S3 print method for an object of class 'psFit'
print.psPosterior	Print a fitPS posterior object
print.summary.psBayesianBootstrap	Summarise a fitPS Bayesian Bootstrap object
print.summary.psBootstrap	Summarise a fitPS bootstrap object
print.summary.psPosterior	Summarise a fitPS posterior object
probfun	Plug-in probability functions
psModel	Construct a public fitPS model descriptor
Psurveys	Number of Groups of Glass Data

-- R --

readData	Read count data from file
rzeta	Generate random variates from a zeta distribution
rZIzeta	Generate zero inflated zeta random variates
rzizeta	Generate zero inflated zeta random variates

-- S --

Ssurveys	Size of Groups of Glass Data
summary.psBayesianBootstrap	Summarise a fitPS Bayesian Bootstrap object
summary.psBootstrap	Summarise a fitPS bootstrap object
summary.psFit	S3 summary method for an object of class 'psFit'
summary.psPosterior	Summarise a fitPS posterior object
supportedPosteriorEngines	Return posterior engines supported by a fitPS model.

-- V --

var	Variance generic
var.default	Variance generic
var.psData	An S3 method for computing the variance of clothing survey for the number of groups or size of groups

-- Z --

zetaModel	Construct built-in fitPS model descriptors
zizModel	Construct built-in fitPS model descriptors

-- misc --

==.psData

S3 method for objects of class 'psData'