mcse.q.mat: Apply 'mcse.q' to each column of a matrix or data frame of...
In statvats/mcmcse: Monte Carlo Standard Errors for MCMC

Description Usage Arguments Value See Also

Apply mcse.q to each column of a matrix or data frame of MCMC samples.

1	mcse.q.mat(x, q, size = NULL, g = NULL, method = c("bm", "obm", "sub"))

`x`	a matrix or data frame with each row being a draw from the multivariate distribution of interest.
`q`	the quantile of interest.
`size`	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.
`g`	a function such that the qth 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.
`method`	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 jth row of the matrix contains the result of applying mcse.q to the jth column of x.

mcse.q, which acts on a vector.

mcse and mcse.mat, which compute standard errors for expectations.

statvats/mcmcse documentation built on Sept. 12, 2021, 8:22 p.m.