cdf_post: cdf_post

In ashr: Methods for Adaptive Shrinkage, using Empirical Bayes

cdf_post

Description

evaluate cdf of posterior distribution of beta at c. m is the prior on beta, a mixture; c is location of evaluation assumption is betahat | beta ~ t_v(beta,sebetahat)

Usage

cdf_post(m, c, data)

Arguments

m	mixture distribution with k components
c	a scalar
data	details depend on model

Value

an n vector containing the cdf for beta_i at c

Examples

beta = rnorm(100,0,1)
betahat= beta+rnorm(100,0,1)
sebetahat=rep(1,100)
ash.beta = ash(betahat,1,mixcompdist="normal")
cdf0 = cdf_post(ash.beta$fitted_g,0,set_data(betahat,sebetahat))
graphics::plot(cdf0,1-get_pp(ash.beta))

ashr documentation built on Aug. 22, 2023, 1:07 a.m.