Description Usage Arguments Examples
Simulates realisations from the posterior distribution for the index and shape parameters in a gamma distribution based on a random sample and independent gamma priors by using a Metropolis within Gibbs algorithm and a normal random walk proposal for the index parameter
1 2 |
N |
length of MCMC chain |
initial |
starting value for the algorithm |
innov |
standard deviation of normal random walk innovation for index parameter |
priorparam |
prior parameters a,b,c,d |
n |
size of random sample |
xbar |
(arithmetic) mean of random sample |
xgbar |
geometric mean of random sample |
show |
logical. If true then acceptance rate for the proposals will be given |
1 | mcmcAnalysis(mwgGamma(100,(0.62/0.4)^2,0.8,c(2,1,3,1),50,0.62,0.46),rows=2)
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