olbm {mcmc} | R Documentation |
Variance of sample mean of time series calculated using overlapping batch means.
olbm(x, batch.length, demean = TRUE)
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. |
The estimated variance of the sample mean.
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)