# Example for Jags-Ydich-XnomSsubj-MbinomBetaOmegaKappa.R
#-------------------------------------------------------------------------------
# Optional generic preliminaries:
#graphics.off() # This closes all of R's graphics windows.
#rm(list=ls()) # Careful! This clears all of R's memory!
#-------------------------------------------------------------------------------
JagsYdichXnomSsubjMbinomBetaOmegaKappa <- function()
{
out <- list()
# Read The data file:
out$myData = read.csv(system.file("data", "TherapeuticTouchData.csv", package = "dbda"))
out$yName = "y" # column name for 0,1 values
out$sName = "s" # column name for subject ID
# Optional: Specify filename root and graphical format for saving output.
# Otherwise specify as NULL or leave saveName and saveType arguments
# out of function calls.
out$fileNameRoot = "Jags-Ydich-XnomSsubj-MbernBetaOmegaKappa-"
out$graphFileType = "eps"
out$numSavedSteps = 1000 # 20000
out$thinSteps = 10
oldClass(out) <- "JagsYdichXnomSsubjMbinomBetaOmegaKappa"
return(out)
}
mod <- JagsYdichXnomSsubjMbinomBetaOmegaKappa()
#-------------------------------------------------------------------------------
# Generate the MCMC chain:
startTime = proc.time()
out = genMCMC(mod, data=mod$myData , sName=mod$sName , yName=mod$yName ,
numSavedSteps=mod$numSavedSteps , saveName=mod$saveName ,
thinSteps=mod$thinSteps )
stopTime = proc.time()
show( stopTime-startTime )
stop()
#-------------------------------------------------------------------------------
# Display diagnostics of chain, for specified parameters:
parameterNames = varnames(mcmcCoda) # get all parameter names for reference
for ( parName in parameterNames[c(1:3,length(parameterNames))] ) {
diagMCMC( codaObject=mcmcCoda , parName=parName ,
saveName=fileNameRoot , saveType=graphFileType )
}
#-------------------------------------------------------------------------------
# Get summary statistics of chain:
summaryInfo = smryMCMC( mcmcCoda , compVal=0.5 ,
diffIdVec=c(1,14,28), compValDiff=0.0,
saveName=fileNameRoot )
# Display posterior information:
plotMCMC( mcmcCoda , data=myData , sName="s" , yName="y" ,
compVal=0.5 , #rope=c(0.45,0.55) ,
diffIdVec=c(1,14,28), compValDiff=0.0, #ropeDiff = c(-0.05,0.05) ,
saveName=fileNameRoot , saveType=graphFileType )
#-------------------------------------------------------------------------------
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.