normal.PP.FB.MC: Normal power prior with full Bayes by Monte Carlo

In StudyPrior: Distributions for Historical Information

Description

Normal power prior with full Bayes by Monte Carlo

Usage

normal.PP.FB.MC(x, sd, verbose = FALSE, length = 30, d.prior.a = 1,
  d.prior.b = 1, mc.cores = 1, samples = 10000, focus)

Arguments

x	numeric vector of results
sd	standard deviations
verbose	Print messages
length	Number of points to evaluate density at
d.prior.a	shape1 parameter for beta prior on weights
d.prior.b	shape2 parameter for beta prior on weights
mc.cores	Number of cores for parallel
samples	Number of Monte Carlo samples
focus	List of triples specifying regions to focus on, eg peaks. Specified as list(c(lower, upper, length))

Value

Density function

StudyPrior documentation built on May 2, 2019, 5:54 p.m.