binom.PP.FB.MC.COR: Full Bayes Power Prior with Correlated Weight Parameters

In StudyPrior: Distributions for Historical Information

Description

Full Bayes Power Prior with Correlated Weight Parameters

Usage

binom.PP.FB.MC.COR(x, n, verbose = FALSE, length = 200, d.prior.cor = 0,
  p.prior.a = 1, p.prior.b = 1, mc.cores = 1, samples = 10000, focus)

Arguments

x	number of historical successes
n	number historical patients
verbose	Print messages
length	Number of points to evaluate density at
d.prior.cor	Correlation parameter for transformed multivariate normal prior on weights
p.prior.a	shape1 parameter for initial beta prior on probability
p.prior.b	shape2 parameter for initial beta prior on probability
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

A density function

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