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)
olbm(out$batch, 150)
# monte carlo estimates (true means are same by symmetry)
apply(out$batch, 1, mean)
# monte carlo standard errors (true s. d. are same by symmetry)
sqrt(diag(olbm(out$batch, 150)))
# check that batch length is reasonable
acf(out$batch, lag.max = 200)