BayesianRegressionMCMCSave <- read.table("C:/Sync/Box/My Box Files/Important_Projects/BernankeRobust/Program/ver0.3/BayesianRegression/BayesianRegressionMCMCSave.RData", quote="\"")
graphics.off()          # Clears all graphical displays.
rm(list=ls(all=TRUE))   # Removes all variables from memory!
# Get the Bayesian functions into R's working memory:
source("BMLR.R")
Regression1 = read.csv( file="../../../Data/DatasetsForPrograms/Regression1.csv" )
Regression2 = read.csv( file="../../../Data/DatasetsForPrograms/Regression2.csv" )
Regression3 = read.csv( file="../../../Data/DatasetsForPrograms/Regression3.csv" )
Regression4 = read.csv( file="../../../Data/DatasetsForPrograms/Regression4.csv" )
mcmcChain1 = BMLRmcmc( Regression1 )
mcmcChain2 = BMLRmcmc( Regression2 )
mcmcChain3 = BMLRmcmc( Regression3 )
mcmcChain4 = BMLRmcmc( Regression4 )
postInfo1 = BMLRplot( mcmcChain1, names=c("YL1","YL2","MRes","MResL1","MResL2","MResL3") )
postInfo2 = BMLRplot( mcmcChain2, names=c("YL1","YL2","PRes","PResL1","PResL2","PResL3") )
postInfo3 = BMLRplot( mcmcChain3, names=c("YL1","YL2","MRes","MResL1","MResL2","MResL3","DBanks","DBanksL1","DFail","DFailL1") )
postInfo4 = BMLRplot( mcmcChain4, names=c("YL1","YL2","PRes","PResL1","PResL2","PResL3","DBanks","DBanksL1","DFail","DFailL1") )
