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runireg=
function(Data,Prior,Mcmc)
{
#
# revision history:
# P. Rossi 1/17/05
# revised 9/05 to put in Data,Prior,Mcmc calling convention
# 3/07 added classes
# W. Taylor 4/15 - added nprint option to MCMC argument
# Purpose:
# perform iid draws from posterior of regression model using
# conjugate prior
#
# Arguments:
# Data -- list of data
# y,X
# Prior -- list of prior hyperparameters
# betabar,A prior mean, prior precision
# nu, ssq prior on sigmasq
# Mcmc -- list of MCMC parms
# R number of draws
# keep -- thinning parameter
# nprint - print estimated time remaining on every nprint'th draw
#
# Output:
# list of beta, sigmasq
#
# Model:
# y = Xbeta + e e ~N(0,sigmasq)
# y is n x 1
# X is n x k
# beta is k x 1 vector of coefficients
#
# Priors: beta ~ N(betabar,sigmasq*A^-1)
# sigmasq ~ (nu*ssq)/chisq_nu
#
#
# check arguments
#
if(missing(Data)) {pandterm("Requires Data argument -- list of y and X")}
if(is.null(Data$X)) {pandterm("Requires Data element X")}
X=Data$X
if(is.null(Data$y)) {pandterm("Requires Data element y")}
y=Data$y
nvar=ncol(X)
nobs=length(y)
#
# check data for validity
#
if(nobs != nrow(X) ) {pandterm("length(y) ne nrow(X)")}
#
# check for Prior
#
if(missing(Prior))
{ betabar=c(rep(0,nvar)); A=BayesmConstant.A*diag(nvar); nu=BayesmConstant.nu; ssq=var(y)}
else
{
if(is.null(Prior$betabar)) {betabar=c(rep(0,nvar))}
else {betabar=Prior$betabar}
if(is.null(Prior$A)) {A=BayesmConstant.A*diag(nvar)}
else {A=Prior$A}
if(is.null(Prior$nu)) {nu=BayesmConstant.nu}
else {nu=Prior$nu}
if(is.null(Prior$ssq)) {ssq=var(y)}
else {ssq=Prior$ssq}
}
#
# check dimensions of Priors
#
if(ncol(A) != nrow(A) || ncol(A) != nvar || nrow(A) != nvar)
{pandterm(paste("bad dimensions for A",dim(A)))}
if(length(betabar) != nvar)
{pandterm(paste("betabar wrong length, length= ",length(betabar)))}
#
# check MCMC argument
#
if(missing(Mcmc)) {pandterm("requires Mcmc argument")}
else
{
if(is.null(Mcmc$R))
{pandterm("requires Mcmc element R")} else {R=Mcmc$R}
if(is.null(Mcmc$keep)) {keep=BayesmConstant.keep} else {keep=Mcmc$keep}
if(is.null(Mcmc$nprint)) {nprint=BayesmConstant.nprint} else {nprint=Mcmc$nprint}
if(nprint<0) {pandterm('nprint must be an integer greater than or equal to 0')}
}
#
# print out problem
#
cat(" ", fill=TRUE)
cat("Starting IID Sampler for Univariate Regression Model",fill=TRUE)
cat(" with ",nobs," observations",fill=TRUE)
cat(" ", fill=TRUE)
cat("Prior Parms: ",fill=TRUE)
cat("betabar",fill=TRUE)
print(betabar)
cat("A",fill=TRUE)
print(A)
cat("nu = ",nu," ssq= ",ssq,fill=TRUE)
cat(" ", fill=TRUE)
cat("MCMC parms: ",fill=TRUE)
cat("R= ",R," keep= ",keep," nprint= ",nprint,fill=TRUE)
cat(" ",fill=TRUE)
###################################################################
# Keunwoo Kim
# 08/05/2014
###################################################################
draws = runireg_rcpp_loop(y, X, betabar, A, nu, ssq, R, keep, nprint)
###################################################################
attributes(draws$betadraw)$class=c("bayesm.mat","mcmc")
attributes(draws$betadraw)$mcpar=c(1,R,keep)
attributes(draws$sigmasqdraw)$class=c("bayesm.mat","mcmc")
attributes(draws$sigmasqdraw)$mcpar=c(1,R,keep)
return(draws)
}
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