mcse to each column of the MCMC samples.Apply mcse to each column of the MCMC samples.
mcse.mat(x, size = NULL, g = NULL, method = "bm", r = 3)a matrix of values from a Markov chain of size n x p.
represents the batch size in “bm” and the truncation point in “bartlett” and
“tukey”. Default is NULL which implies that an optimal batch size is calculated using the
batchSize function. Can take character values of “sqroot” and “cuberoot” or any numeric
value between 1 and n/2. “sqroot” means size is \(\lfloor n^{1/2} \rfloor\) and “cuberoot” means size is
\(\lfloor n^{1/3} \rfloor\).
a function such that \(E(g(x))\) is the quantity of interest. The default is
NULL, which causes the identity function to be used.
any of “bm”,“obm”,“bartlett”, “tukey”. “bm”
represents batch means estimator, “obm” represents overlapping batch means estimator with, “bartlett”
and “tukey” represents the modified-Bartlett window and the Tukey-Hanning windows for spectral variance estimators.
The lugsail parameters (r) that converts a lag window into its lugsail
equivalent. Larger values of r will typically imply less underestimation of “cov”,
but higher variability of the estimator. Default is r = 3 and r = 1,2 are
also good choices although may lead to underestimates of the variance. r > 5 is not recommended.
mcse.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 to the \(j\)th column of x.
mcse, which acts on a vector.
mcse.multi, for a multivariate estimate of the Monte Carlo standard error.
mcse.q and mcse.q.mat, which compute standard errors for quantiles.