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bayescount (version 0.9.99-9)

Power Calculations and Bayesian Analysis of Count Distributions and FECRT Data using MCMC

Description

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.

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Version

Install

install.packages('bayescount')

Monthly Downloads

397

Version

0.9.99-9

License

GPL-2

Maintainer

Last Published

December 8th, 2023

Functions in bayescount (0.9.99-9)

fec.analysis

Analyse Count data using MCMC
likelihood

Calculate the (Log) Likelihood of Obtaining Data from a Distribution
lnormal.params

Calculate the Log-Normal Mean and Standard Deviation Using the Normal Mean and Standard Deviation
fecrt.model

Create an MCMC model to analyse FECRT Data
fecrt.power

FECRT Power Analysis Calculations
fecrt.analysis

Analyse FECRT Data Using MCMC to Give a Probability Distribution of Values for the Mean Egg Count Reduction
bayescount

Analyse Count data using MCMC
count.precision

Count Data Predicted Precision Calculations
normal.params

Calculate the Normal Mean and Standard Deviation Using the Log-Normal Mean and Standard Deviation
count.power

Count Data Power Analysis Calculations
maximise.likelihood

Calculate the Maximum Likelihood Parameters of a Continuous or Count Distribution
count.model

Analyse Count Data Using Jags
fecrt.precision

FECRT Predicted Precision Calculations