Prior_y: Prior predictive distribution of the count in the control...

In stla/brr: Bayesian Inference on the Ratio of Two Poisson Rates

Description

Density, distribution function, quantile function and random generation for the prior predictive distribution of the count in the control group.

Usage

dprior_y(y, a, b, T, ...)

pprior_y(q, a, b, T, ...)

qprior_y(p, a, b, T, ...)

rprior_y(n, a, b, T)

sprior_y(a, b, T, ...)

Arguments

y,q	vector of non-negative integer quantiles
a,b	non-negative shape parameter and rate parameter of the Gamma prior distribution on the rate μ
T	sample size of the control group
...	other arguments passed to NegBinomial or summary_nbinom (for sprior_y)
p	vector of probabilities
n	number of observations to be simulated

Details

The prior predictive distribution of the count y is the Poisson-Gamma distribution with shape parameter a and hyperrate parameter b/T, which is also the negative binomial distribution with shape a and probability of success b/(b+T).

Value

dprior_y gives the density, pprior_y the distribution function, qprior_y the quantile function, rprior_y samples from the distribution, and sprior_y gives a summary of the distribution.

Note

Prior_y is a generic name for the functions documented.

Examples

barplot(dprior_y(0:10, 2, 2, 1))
sprior_y(2, 2, 1, output="pandoc")

stla/brr documentation built on May 30, 2019, 5:46 p.m.