R: Overlapping Batch Means

olbm {mcmc} | R Documentation

## 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)

[Package mcmc version 0.9-7 Index]