get_posterior_mean: Compute the full conditional (given tau, rho, and data) mean...

In rtlemos/scallops: Lemos and Sanso' (2012) model, edited for speed

Description

Compute the full conditional (given tau, rho, and data) mean of gamma

Usage

get_posterior_mean(prior_mean, prior_precision, posterior_precision,
  kernel_matrix, tau, y)

Arguments

prior_mean	Prior mean of gamma
prior_precision	Prior precision of gamma
posterior_precision	Full conditional precision of gamma
kernel_matrix	DPC kernel matrix
tau	Sampled value of tau
y	Data

Examples

km = list(mat = Matrix::Diagonal(2, 1))
prior_pr = Matrix::Diagonal(2, 0.3)
tau = 5
post_pr = get_posterior_precision(prior_pr, km, tau)
get_posterior_mean(prior_mean = rep(0, 2), prior_precision = prior_pr, 
                   posterior_precision = post_pr, kernel_matrix = km, tau = tau, y = c(0.9, 0.7))

rtlemos/scallops documentation built on May 4, 2019, 7:43 p.m.