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 = NULL, g = NULL, method = c("bm", "obm", "sub"))
a matrix or data frame with each row being a draw from the multivariate distribution of interest.
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.