PPCteststatistics {bayesplot}  R Documentation 
The distribution of a (test) statistic T(yrep)
, or a pair of (test)
statistics, over the simulated datasets in yrep
, compared to the
observed value T(y)
computed from the data y
. See the
Plot Descriptions and Details sections, below, as
well as Gabry et al. (2019).
ppc_stat(
y,
yrep,
stat = "mean",
...,
binwidth = NULL,
bins = NULL,
breaks = NULL,
freq = TRUE
)
ppc_stat_grouped(
y,
yrep,
group,
stat = "mean",
...,
facet_args = list(),
binwidth = NULL,
bins = NULL,
breaks = NULL,
freq = TRUE
)
ppc_stat_freqpoly(
y,
yrep,
stat = "mean",
...,
facet_args = list(),
binwidth = NULL,
bins = NULL,
freq = TRUE
)
ppc_stat_freqpoly_grouped(
y,
yrep,
group,
stat = "mean",
...,
facet_args = list(),
binwidth = NULL,
bins = NULL,
freq = TRUE
)
ppc_stat_2d(y, yrep, stat = c("mean", "sd"), ..., size = 2.5, alpha = 0.7)
ppc_stat_data(y, yrep, group = NULL, stat)
y 
A vector of observations. See Details. 
yrep 
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.
ppc_stat()
, ppc_stat_freqpoly()
A histogram or frequency polygon of the distribution of a statistic
computed by applying stat
to each dataset (row) in yrep
. The value of
the statistic in the observed data, stat(y)
, is overlaid as a vertical
line. More details and example usage of ppc_stat()
can be found in Gabry
et al. (2019).
ppc_stat_grouped()
,ppc_stat_freqpoly_grouped()
The same as ppc_stat()
and ppc_stat_freqpoly()
, but a separate plot is
generated for each level of a grouping variable. More details and example
usage of ppc_stat_grouped()
can be found in Gabry et al. (2019).
ppc_stat_2d()
A scatterplot showing the joint distribution of two statistics
computed over the datasets (rows) in yrep
. The value of the
statistics in the observed data is overlaid as large point.
Gabry, J. , Simpson, D. , Vehtari, A. , Betancourt, M. and Gelman, A. (2019), Visualization in Bayesian workflow. J. R. Stat. Soc. A, 182: 389402. doi:10.1111/rssa.12378. (journal version, arXiv preprint, code on GitHub)
Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., and Rubin, D. B. (2013). Bayesian Data Analysis. Chapman & Hall/CRC Press, London, third edition. (Ch. 6)
Other PPCs:
PPCcensoring
,
PPCdiscrete
,
PPCdistributions
,
PPCerrors
,
PPCintervals
,
PPCloo
,
PPCoverview
,
PPCscatterplots
y < example_y_data()
yrep < example_yrep_draws()
ppc_stat(y, yrep)
ppc_stat(y, yrep, stat = "sd") + legend_none()
# use your own function for the 'stat' argument
color_scheme_set("brightblue")
q25 < function(y) quantile(y, 0.25)
ppc_stat(y, yrep, stat = "q25") # legend includes function name
# can define the function in the 'stat' argument instead of
# using its name but then the legend doesn't include the function name
ppc_stat(y, yrep, stat = function(y) quantile(y, 0.25))
# plots by group
color_scheme_set("teal")
group < example_group_data()
ppc_stat_grouped(y, yrep, group)
ppc_stat_grouped(y, yrep, group) + yaxis_text()
# force yaxes to have same scales, allow x axis to vary
ppc_stat_grouped(y, yrep, group, facet_args = list(scales = "free_x")) + yaxis_text()
# the freqpoly plots use frequency polygons instead of histograms
ppc_stat_freqpoly(y, yrep, stat = "median")
ppc_stat_freqpoly_grouped(y, yrep, group, stat = "median", facet_args = list(nrow = 2))
# ppc_stat_2d allows 2 statistics and makes a scatterplot
bayesplot_theme_set(ggplot2::theme_linedraw())
color_scheme_set("viridisE")
ppc_stat_2d(y, yrep, stat = c("mean", "sd"))
bayesplot_theme_set(ggplot2::theme_grey())
color_scheme_set("brewerPaired")
ppc_stat_2d(y, yrep, stat = c("median", "mad"))
# reset aesthetics
color_scheme_set()
bayesplot_theme_set()