Prior_lambda: Prior distribution on the incidence rate in the treated group

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

Description

Density, distribution function (see Details) and random generation for the prior distribution on the rate in the treated group. The prior distribution on the incidence rate λ is not to be set by the user: it is induced by the user-specified prior on μ and φ.

Usage

dprior_lambda(lambda, a, b, c, d, S, T)

rprior_lambda(n, a, b, c, d, S, T)

pprior_lambda(q, a, b, c, d, S, T, ...)

sprior_lambda(a, b, c, d, S, T, ...)

Arguments

lambda,q	vector of quantiles
a,b	non-negative shape and rate parameter of the Gamma prior distribution on μ
c,d	non-negative shape parameters of the prior distribution on φ
S,T	sample sizes in control group and treated group
n	number of observations to be simulated
...	other arguments passed to genhypergeo through pGB2, such as series=FALSE to use the continued fraction expansion, or passed to summary_GB2 (for sprior_lambda)

Details

The pdf of the prior distribution on the incidence rate λ involves the Kummer confluent hypergeometric function of the second kind. The cdf involves the generalized hypergeometric function. Its current implementation does not work when a-c is an integer.

Value

dprior_lambda gives the density, pprior_lambda the distribution function (see Details), rprior_lambda samples from the distribution, and rprior_lambda gives a summary of the distribution.

Note

Prior_lambda is a generic name for the functions documented.

Examples

curve(dprior_lambda(x, 2, 2, 2.5, 2, 10, 10), from=0, to=5)
sprior_lambda(2, 2, 2.5, 2, 10, 10)

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