PPD-test-statistics | R Documentation |
The distribution of a (test) statistic T(ypred)
, or a pair of (test)
statistics, over the simulations from the posterior or prior predictive
distribution. Each of these functions makes the same plot as the
corresponding ppc_
function but without comparing to
any observed data y
. The Plot Descriptions section at
PPC-test-statistics has details on the individual plots.
ppd_stat(
ypred,
stat = "mean",
...,
binwidth = NULL,
bins = NULL,
breaks = NULL,
freq = TRUE
)
ppd_stat_grouped(
ypred,
group,
stat = "mean",
...,
facet_args = list(),
binwidth = NULL,
bins = NULL,
breaks = NULL,
freq = TRUE
)
ppd_stat_freqpoly(
ypred,
stat = "mean",
...,
facet_args = list(),
binwidth = NULL,
bins = NULL,
freq = TRUE
)
ppd_stat_freqpoly_grouped(
ypred,
group,
stat = "mean",
...,
facet_args = list(),
binwidth = NULL,
bins = NULL,
freq = TRUE
)
ppd_stat_2d(ypred, stat = c("mean", "sd"), ..., size = 2.5, alpha = 0.7)
ppd_stat_data(ypred, group = NULL, stat)
ypred |
An |
stat |
A single function or a string naming a function, except for the 2D plot which requires a vector of exactly two names or functions. In all cases the function(s) should take a vector input and return a scalar statistic. If specified as a string (or strings) then the legend will display the function name(s). If specified as a function (or functions) then generic naming is used in the legend. |
... |
Currently unused. |
binwidth |
Passed to |
bins |
Passed to |
breaks |
Passed to |
freq |
For histograms, |
group |
A grouping variable of the same length as |
facet_args |
A named list of arguments (other than |
size , alpha |
For the 2D plot only, arguments passed to
|
For Binomial data, the plots may be more useful if the input contains the "success" proportions (not discrete "success" or "failure" counts).
The plotting functions return a ggplot object that can be further
customized using the ggplot2 package. The functions with suffix
_data()
return the data that would have been drawn by the plotting
function.
Gabry, J. , Simpson, D. , Vehtari, A. , Betancourt, M. and Gelman, A. (2019), Visualization in Bayesian workflow. J. R. Stat. Soc. A, 182: 389-402. doi:10.1111/rssa.12378. (journal version, arXiv preprint, code on GitHub)
Other PPDs:
PPD-distributions
,
PPD-intervals
,
PPD-overview
yrep <- example_yrep_draws()
ppd_stat(yrep)
ppd_stat(yrep, stat = "sd") + legend_none()
# use your own function for the 'stat' argument
color_scheme_set("brightblue")
q25 <- function(y) quantile(y, 0.25)
ppd_stat(yrep, stat = "q25") # legend includes function name
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