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VPC plot for prediction-interval Campsis output.

Source: R/vpc_plot.R
vpc_plot.pi_campsis_tbl.Rd

Plots VPC ribbons (a confidence interval around the median, lower and upper percentiles) from a pi_campsis_tbl, i.e. the output of simulate() with multiple replicates and a PIOutfun. Such data already contains the per-replicate prediction interval in long format (columns replicate, TIME, metric with values "low" / "med" / "up" and value). This method only needs to compute the confidence interval around each percentile across replicates.

Usage

# S3 method for class 'pi_campsis_tbl'
vpc_plot(x, strata = "auto", level = 0.9, alpha = 0.15, facet = TRUE, ...)

Arguments

x

a pi_campsis_tbl object with a replicate column

strata

stratification for the VPC. One of "auto", NULL, or a named character vector of length 1. See Details.

level

confidence interval level for the ribbons around each percentile. Default is 0.90 (90% CI).

alpha

transparency of the ribbons. Default is 0.15.

facet

how the stratification variable is displayed when present. TRUE (default) draws one panel per stratum; FALSE overlays the strata in a single panel and maps the stratum to the ribbon fill colour. Forwarded to vpcPlot.

...

additional arguments (currently unused, reserved for future use)

Value

a ggplot object

Details

Stratification is resolved as follows:

  • "auto" (default): ARM is used when more than one distinct arm is detected; otherwise SCENARIO is used when more than one distinct scenario is detected; otherwise NULL (no stratification). Only one stratification variable is applied because vpcPlot supports at most one.

  • NULL: no stratification.

  • named character vector: passed directly to vpcPlot (e.g. c(ARM = "all") or c(SCENARIO = "all")).

See also

vpcPlot, PIOutfun