post_summ: Obtain posterior summaries and diagnostics of specific nodes

In bstaton1/codaTools: Utilities for Processing Posterior Samples Stored in 'mcmc.lists'

Obtain posterior summaries and diagnostics of specific nodes

Description

Allows rapid calculation of summaries and diagnostics from specific nodes stored in mcmc.list objects.

Usage

post_summ(
  post,
  params,
  digits = NULL,
  probs = c(0.5, 0.025, 0.975),
  Rhat = FALSE,
  neff = FALSE,
  mcse = FALSE,
  by_chain = FALSE,
  auto_escape = TRUE
)

Arguments

post	A mcmc.list object.
params	A vector of regular expressions specifying the nodes to match for summarization. Accepts multi-element vectors to match more than one node at a time. See match_params() and vignette("pattern-matching") for more details.
digits	Control rounding of summaries. Passed to base::round() and defaults to NULL, which produces no rounding.
probs	Posterior quantiles to calculate. Passed to stats::quantile(). Defaults to probs = c(0.5, 0.025, 0.975) (i.e., median and equal-tailed 95 percent credible interval).
Rhat	Calculate the Rhat convergence diagnostic using coda::gelman.diag()? Fair warning: this can take a bit of time to run on many nodes/samples.
neff	Calculate the number of effective MCMC samples using coda::effectiveSize()? Fair warning: this can take a bit of time to run on many nodes/samples.
mcse	Calculate the Monte Carlo standard error for the posterior mean and reported quantiles using the mcmcse::mcse() and mcmcse::mcse.q() functions (batch means method with batch size automatically calculated)? Fair warning: this can take a bit of time to run on many nodes/samples.
by_chain	Calculate posterior summaries for each chain rather than for the aggregate across chains? Defaults to FALSE. The arguments Rhat, neff, and mcse are ignored if by_chain = TRUE and a warning will be returned.
auto_escape	Automatically escape "[" and "]" characters for pattern matching? See match_params() for details.

Value

A matrix object with summary statistics as rows and nodes as columns. If by_chain = TRUE, an array with chain-specific summaries as the third dimension is returned instead.

See Also

match_params(), coda::gelman.diag(), coda::effectiveSize(), mcmcse::mcse(), mcmcse::mcse.q()

Examples

# load example mcmc.list
data(cjs)

# calculate posterior summaries for the "p" nodes
# ("p[1]" doesn't exist in model)
post_summ(cjs, "p")

# do this by chain
post_summ(cjs, "p", by_chain = TRUE)

# calculate Rhat and Neff diagnostic summaries as well
# multiple node names too
post_summ(cjs, c("b0", "p"), Rhat = TRUE, neff = TRUE)

# calculate Monte Carlo SE for mean and quantiles, with rounding
post_summ(cjs, "p", mcse = TRUE, digits = 3)

# summarize different quantiles: median and central 80%
post_summ(cjs, "p", probs = c(0.5, 0.1, 0.9))

bstaton1/codaTools documentation built on Jan. 1, 2023, 12:17 p.m.