olbm: Overlapping Batch Means

In mcmc: Markov Chain Monte Carlo

Overlapping Batch Means

Description

Variance of sample mean of time series calculated using overlapping batch means.

Usage

olbm(x, batch.length, demean = TRUE)

Arguments

x	a matrix or time series object. Each column of x is treated as a scalar time series.
batch.length	length of batches.
demean	when demean = TRUE (the default) the sample mean is subtracted from each batch mean when estimating the variance. Using demean = FALSE would essentially assume the true mean is known to be zero, which might be useful in a toy problem where the answer is known.

Value

The estimated variance of the sample mean.

See Also

ts

Examples

h <- function(x) if (all(x >= 0) && sum(x) <= 1) return(1) else return(-Inf)
out <- metrop(h, rep(0, 5), 1000)
out <- metrop(out, scale = 0.1)
out <- metrop(out, nbatch = 1e4)
foo <- olbm(out$batch, 150)
# monte carlo estimates (true means are same by symmetry)
apply(out$batch, 2, mean)
# monte carlo standard errors (true s. d. are same by symmetry)
sqrt(diag(foo))
# check that batch length is reasonable
acf(out$batch, lag.max = 200)

mcmc documentation built on Nov. 17, 2023, 1:06 a.m.