count_analysis: Count data analysis
In mdenwood/bayescount: Statistical Analyses and Power Calculations for Count Data and Faecal Egg Count Reduction Tests (FECRT)
View source: R/count_analysis.R
Description
Analyses count data for difference to either known or fixed mean using any of (1) Christian approach, (2) my approach, (3) bootstrap, (4) MCMC (default 1-3). (4) calls count_model and then runs the model using runjags, and is the only one to permit ZI and LP. Requires Just Another Gibbs Sampler (JAGS) (see http://mcmc-jags.sourceforge.net)
Usage
1
2
3
count_analysis(data = stop("Data must be specified"), model = "ZILP",
alt.prior = FALSE, adjust.zi.mean = FALSE, raw.output = FALSE,
likelihood = FALSE, ...)
See Also
count_model, reduction_analysis, bayescount, autoextend.jags, runjags
mdenwood/bayescount documentation built on Oct. 17, 2019, 6:59 a.m.
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View source: R/count_analysis.R
Description
Analyses count data for difference to either known or fixed mean using any of (1) Christian approach, (2) my approach, (3) bootstrap, (4) MCMC (default 1-3). (4) calls count_model and then runs the model using runjags, and is the only one to permit ZI and LP. Requires Just Another Gibbs Sampler (JAGS) (see http://mcmc-jags.sourceforge.net)
Usage
1 2 3 | count_analysis(data = stop("Data must be specified"), model = "ZILP",
alt.prior = FALSE, adjust.zi.mean = FALSE, raw.output = FALSE,
likelihood = FALSE, ...)
|
See Also
count_model, reduction_analysis, bayescount, autoextend.jags, runjags
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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