Get a single graphic of basic NPDE diagnostics (npde_panel()) or get the component plots in a list that can be arranged by the user (npde_panel_list()) . See npde_covariate() for plotting NPDE versus covariates.

npde_panel(
  df,
  xname = "value",
  unit_time = "hours",
  unit_tad = "hours",
  xby_time = NULL,
  xby_tad = NULL,
  tag_levels = NULL
)

npde_panel_list(
  df,
  xname = "value",
  unit_time = "hours",
  unit_tad = "hours",
  xby_time = NULL,
  xby_tad = NULL
)

Arguments

df

a data frame to plot.

xname

passed to npde_pred().

unit_time

passed to npde_tad() as xunit.

unit_tad

passed to npde_time() as xunit.

xby_time

passed to npde_time() as xby.

xby_tad

passed to npde_tad() as xby.

tag_levels

passed to patchwork::plot_annotation().

Value

npde_panel() returns a single graphic as a patchwork object with the following panels:

npde_panel_list() returns a list of the individual plots that are incorporated into the npde_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.

See also

Examples

data <- pmplots_data_obs()
npde_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 <- npde_panel_list(data)
names(l)
#> [1] "time" "tad"  "hist" "q"    "pred"
with(l, (q+hist) / pred, tag_levels = "a")
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
#> `geom_smooth()` using formula = 'y ~ x'