Random walk Metropolis algorithm of a posterior distribution
Simulates iterates of a random walk Metropolis chain for an arbitrary real-valued posterior density defined by the user
rwmetrop(logpost,proposal,start,m,...)
logpost |
function defining the log posterior density |
proposal |
a list containing var, an estimated variance-covariance matrix, and scale, the Metropolis scale factor |
start |
vector containing the starting value of the parameter |
m |
the number of iterations of the chain |
... |
data that is used in the function logpost |
par |
a matrix of simulated values where each row corresponds to a value of the vector parameter |
accept |
the acceptance rate of the algorithm |
Jim Albert
data=c(6,2,3,10) varcov=diag(c(1,1)) proposal=list(var=varcov,scale=2) start=array(c(1,1),c(1,2)) m=1000 s=rwmetrop(logctablepost,proposal,start,m,data)
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