Get a single graphic of basic CWRES
diagnostics (cwres_panel()
) or get
the component plots in a list that can be arranged by the user
(cwres_panel_list()
) . See cwres_covariate()
for plotting CWRES
versus covariates.
cwres_panel(
df,
xname = "value",
unit_time = "hours",
unit_tad = "hours",
xby_time = NULL,
xby_tad = NULL,
tag_levels = NULL
)
cwres_panel_list(
df,
xname = "value",
unit_time = "hours",
unit_tad = "hours",
xby_time = NULL,
xby_tad = NULL
)
a data frame to plot.
passed to npde_pred()
.
passed to npde_tad()
as xunit
.
passed to npde_time()
as xunit
.
passed to npde_time()
as xby
.
passed to npde_tad()
as xby
.
passed to patchwork::plot_annotation()
.
cwres_panel()
returns a single graphic with the following panels:
CWRES
versus TIME
via cwres_time()
CWRES
versus TAD
via cwres_tad()
CWRES
versus PRED
via cwres_pred()
CWRES
histogram via cwres_hist()
CWRES
quantile-quantile plot via cwres_q()
cwres_panel_list()
returns a list of the individual plots that are
incorporated into the cwres_panel()
output. Each element of the list
is named for the plot in that position: time
, tad
, pred
, hist
q
. See Examples for how you can work with that list.
data <- pmplots_data_obs()
cwres_panel(data, tag_levels = "A")
#> `geom_smooth()` using formula = 'y ~ x'
#> `geom_smooth()` using formula = 'y ~ x'
#> `geom_smooth()` using formula = 'y ~ x'
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
l <- cwres_panel_list(data)
with(l, (q+hist) / pred)
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
#> `geom_smooth()` using formula = 'y ~ x'