mcmc_dm ObjectsSummary and corresponding print methods for objects of the class mcmc_dm,
resulting from a call to estimate_bayesian(). mcmc_dm
objects contain MCMC samples for Bayesian parameter estimation of
drift_dm() objects. The summary includes basic parameter
statistics, quantiles, Gelman-Rubin diagnostics, and effective sample sizes.
# S3 method for mcmc_dm
summary(object, ..., id = NULL)# S3 method for summary.mcmc_dm
print(
x,
...,
round_digits = drift_dm_default_rounding(),
show_statistics = TRUE,
show_quantiles = FALSE,
show_gr = TRUE,
show_eff_n = TRUE
)
summary.mcmc_dm() returns an object of class summary.mcmc_dm,
which is a list with the following entries:
general: General information about the MCMC run.
statistics: Basic parameter summary statistics.
quantiles: Quantiles for each parameter.
gr: Gelman-Rubin diagnostics.
eff_n: Effective sample sizes.
print.summary.mcmc_dm() prints selected summary components and returns the
input object invisibly.
an object of class mcmc_dm, as returned by
estimate_bayesian()
additional arguments passed forward to
coda::summary.mcmc.list().
optional single numeric or character, specifying one or more
participant IDs to subset object in the hierarchical case. Note that id
will be converted to character, because dimension names of the chains stored
in object are character. If NULL, then the function is applied to
group-level parameters.
an object of class summary.mcmc_dm, as returned by
summary.mcmc_dm().
an integer, defining the number of digits for rounding the output.
a logical, if TRUE, print basic parameter
statistics (means, SDs, standard errors).
a logical, if TRUE, print quantile summary.
a logical; if TRUE, print Gelman-Rubin convergence
diagnostics for each parameter.
a logical, if TRUE, print effective sample sizes for
each parameter.
The summary and diagnostic statistics of the MCMC chains are obtained
using the R package coda.
coda::gelman.diag(), coda::effectiveSize(),
coda::summary.mcmc.list()
mcmc_obj <- get_example_fits("mcmc_dm")
print(mcmc_obj)
summary(mcmc_obj)
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