sur_sample_gibbs_cpp {surbayes}

Power Prior Gibbs sampling

Description

This is a c++ implementation of Gibbs sampling SUR model with power prior

Usage

sur_sample_gibbs_cpp(
  Sigma,
  M,
  X,
  X0,
  XtX,
  X0tX0,
  Y,
  Y0,
  y,
  y0,
  a0,
  pvec,
  burnin,
  thin
)

Arguments

Sigma

initial value for covariance matrix

M

number of samples

X

design matrix for current data

X0

design matrix for historical data

XtX

matrix that is crossprod(cbind(X1, ..., XJ))

X0tX0

matrix that is crossprod(cbind(X01, ..., X0J))

Y

future response as matrix (Y1, ..., YJ)

Y0

historical response as matrix (Y01, ..., Y0J)

y

future response as vector

y0

historical response as vector

a0

power prior parameter

pvec

vector giving number of covariates per endpoint

burnin

Burn-in parameter

thin

Thin parameter

Value

sampled covariance matrix