mcse.q to each column of a matrix or data frame of MCMC samples.Apply mcse.q to each column of a matrix or data
frame of MCMC samples.
mcse.q.mat(x, q, size = "sqroot", g = NULL,
method = c("bm", "obm", "sub"))a matrix or data frame of Markov chain output. Number of rows is the Monte Carlo sample size.
the quantile of interest.
the batch size. The default value is
“sqroot”, which uses the square root of the
sample size. “cuberoot” will cause the
function to use the cube root of the sample size. A
numeric value may be provided if “sqroot”
is not satisfactory.
a function such that the \(q\)th quantile of
the univariate distribution function of \(g(x)\) is the
quantity of interest. The default is NULL, which
causes the identity function to be used.
the method used to compute the standard
error. This is one of “bm” (batch means,
the default), “obm” (overlapping batch
means), or “sub” (subsampling bootstrap).
mcse.q.mat returns a matrix with ncol(x)
rows and two columns. The row names of the matrix are the
same as the column names of x. The column names of
the matrix are “est” and
“se”. The \(j\)th row of the matrix
contains the result of applying mcse.q to the
\(j\)th column of x.
mcse.q, which acts on a vector.
mcse and mcse.mat, which
compute standard errors for expectations.