Utility functions for MCMC output analysis
Returns the mean, the standard deviation of the mean, and a sequence of partial means of the input vector or matrix.
mcmcMean(x, sd = TRUE) mcmcMeans(x, sd = TRUE) mcmcSD(x) ergMean(x, m = 1)
x |
vector or matrix containing the output of a Markov chain Monte Carlo simulation. |
sd |
logical: should an estimate of the Monte Carlo standard deviation be reported? |
m |
ergodic means are computed for |
The argument x is typically the output from a simulation. If a
matrix, rows are considered consecutive simulations of a target
vector. In this case means, standard deviations, and ergodic means
are returned for each column. The standard deviation of the mean is
estimated using Sokal's method (see the reference). mcmcMeans
is an alias for mcmcMean.
Giovanni Petris GPetris@uark.edu
P. Green (2001). A Primer on Markov Chain Monte Carlo. In Complex Stochastic Systems, (Barndorff-Nielsen, Cox and Kl\"uppelberg, eds.). Chapman and Hall/CRC.
x <- matrix(rexp(1000), nc=4) dimnames(x) <- list(NULL, LETTERS[1:NCOL(x)]) mcmcSD(x) mcmcMean(x) em <- ergMean(x, m = 51) plot(ts(em, start=51), xlab="Iteration", main="Ergodic means")
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