bayescount: Power Calculations and Bayesian Analysis of Count Distributions and FECRT Data using MCMC
Version 0.9.99-5

A set of functions to allow analysis of count data (such as faecal egg count data) using Bayesian MCMC methods. Returns information on the possible values for mean count, coefficient of variation and zero inflation (true prevalence) present in the data. A complete faecal egg count reduction test (FECRT) model is implemented, which returns inference on the true efficacy of the drug from the pre- and post-treatment data provided, using non-parametric bootstrapping as well as using Bayesian MCMC. Functions to perform power analyses for faecal egg counts (including FECRT) are also provided.

Browse man pages Browse package API and functions Browse package files

AuthorMatthew Denwood [aut, cre]
Date of publication2015-04-20 11:46:52
MaintainerMatthew Denwood <md@sund.ku.dk>
LicenseGPL-2
Version0.9.99-5
URL http://bayescount.sourceforge.net
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("bayescount")

Man pages

bayescount: Analyse Count data using MCMC
bayescount.single: Analyse Count data using MCMC
fec.power: Count Data Power Analysis Calculations
fec.power.limits: Count Data Predicted Precision Calculations
fecrt.analysis: Analyse FECRT Data Using MCMC to Give a Probability...
fecrt.model: Create an MCMC model to analyse FECRT Data
fecrt.power: FECRT Power Analysis Calculations
fecrt.power.limits: FECRT Predicted Precision Calculations
likelihood: Calculate the (Log) Likelihood of Obtaining Data from a...
lnormal.params: Calculate the Log-Normal Mean and Standard Deviation Using...
maximise.likelihood: Calculate the Maximum Likelihood Parameters of a Continuous...
normal.params: Calculate the Normal Mean and Standard Deviation Using the...
run.model: Analyse Count Data Using Jags

Functions

FEC.analysis} \alias{bayescount.single Man page
FEC.model Man page
FEC.power Man page
FEC.power.limits Man page
FEC.precision Man page
FECRT Man page
FECRT.analysis Man page
FECRT.model Man page
FECRT.power Man page
FECRT.power.limits Man page
FECRT.precision Man page
assess.variance Source code
bayescount Man page Source code
bayescount.single Source code
binary.search Source code
count.analysis} \alias{fec.analysis Man page
count.model Man page
count.power Man page
count.precision Man page
fec.model Man page
fec.power Man page Source code
fec.power.limits Man page Source code
fec.precision Man page
fecrt Man page
fecrt.analysis Man page Source code
fecrt.model Man page Source code
fecrt.power Man page Source code
fecrt.power.limits Man page Source code
fecrt.precision Man page
geninits Source code
likelihood Man page Source code
lnormal.params Man page Source code
maximise.likelihood Man page Source code
normal.params Man page Source code
print.fecrt.results Source code
run.model Man page Source code
sortfecrtdata Source code

Files

src
src/power.c
NAMESPACE
CHANGELOG
R
R/fec.power.R
R/normal.lnormal.params.R
R/invisible.R
R/bayescount.single.R
R/bayescount.R
R/run.model.R
R/likelihood.R
R/fecrt.model.R
R/fecrt.analysis.R
R/maximise.likelihood.R
R/fecrt.power.R
MD5
DESCRIPTION
man
man/bayescount.single.Rd
man/fecrt.model.Rd
man/lnormal.params.Rd
man/fecrt.power.Rd
man/likelihood.Rd
man/fecrt.power.limits.Rd
man/bayescount.Rd
man/fecrt.analysis.Rd
man/normal.params.Rd
man/fec.power.Rd
man/maximise.likelihood.Rd
man/run.model.Rd
man/fec.power.limits.Rd
bayescount documentation built on May 19, 2017, 2:29 p.m.