draws_summary {posterior} | R Documentation |
draws
objectsThe summarise_draws()
(and summarize_draws()
) methods provide a quick way
to get a table of summary statistics and diagnostics. These methods will
convert an object to a draws
object if it isn't already. For convenience, a
summary() method for draws
and rvar
objects are also
provided as an alias for summarise_draws()
if the input object is a draws
or rvar
object.
summarise_draws(.x, ...) summarize_draws(.x, ...) ## S3 method for class 'draws' summarise_draws( .x, ..., .args = list(), .num_args = getOption("posterior.num_args", list()), .cores = 1 ) ## S3 method for class 'draws' summary(object, ...) ## S3 method for class 'rvar' summarise_draws(.x, ...) ## S3 method for class 'rvar' summary(object, ...) default_summary_measures() default_convergence_measures() default_mcse_measures()
.x, object |
(draws) A |
... |
Name-value pairs of summary or diagnostic functions. The provided names will be used as the names of the columns in the result unless the function returns a named vector, in which case the latter names are used. The functions can be specified in any format supported by as_function(). See Examples. |
.args |
(named list) Optional arguments passed to the summary functions. |
.num_args |
(named list) Optional arguments passed to
num() for pretty printing of summaries. Can be controlled
globally via the |
.cores |
(positive integer) The number of cores to use for computing
summaries for different variables in parallel. Coerced to integer if
possible, otherwise errors. The default is |
The default summary functions used are the ones specified by
default_summary_measures()
and default_convergence_measures()
:
default_summary_measures()
default_convergence_measures()
The var()
function should not be used to compute variances due
to its inconsistent behavior with matrices. Instead, please use
distributional::variance()
.
The summarise_draws()
methods return a tibble data frame.
The first column ("variable"
) contains the variable names and the remaining
columns contain summary statistics and diagnostics.
The functions default_summary_measures()
, default_convergence_measures()
,
and default_mcse_measures()
return character vectors of names of the
default measures.
diagnostics
for a list of available diagnostics and links to
their individual help pages.
x <- example_draws("eight_schools") class(x) str(x) summarise_draws(x) summarise_draws(x, "mean", "median") summarise_draws(x, mean, mcse = mcse_mean) summarise_draws(x, ~quantile(.x, probs = c(0.4, 0.6))) # using default_*_meaures() summarise_draws(x, default_summary_measures()) summarise_draws(x, default_convergence_measures()) summarise_draws(x, default_mcse_measures()) # compute variance of variables summarise_draws(x, var = distributional::variance) # illustrate use of '.args' ws <- rexp(ndraws(x)) summarise_draws(x, weighted.mean, .args = list(w = ws)) # adjust how numerical summaries are printed summarise_draws(x, .num_args = list(sigfig = 2, notation = "dec"))