Here is an example of the code for using the program:
# Specify the data
y = c(101,100,102,104,102,97,105,105,98,101,100,123,105,103,100,95,102,106,
109,102,82,102,100,102,102,101,102,102,103,103,97,97,103,101,97,104,
96,103,124,101,101,100,101,101,104,100,101)
# Run the Bayesian analysis:
source("BEST1G.R")
mcmcChain = BEST1Gmcmc( y )
# Display the results:
BEST1Gplot( y , mcmcChain , compValm=100 , ROPEeff=c(-0.1,0.1) , pairsPlot=TRUE )
The function BEST1Gplot returns detailed numerical summaries of the posterior distribution (not shown here), and it also produces graphical output like this:


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