Skip to contents

Plots panels of cumulative distribution functions (CDFs) for each level of the specified defective factor in the data. The CDFs are defective; each factor level's CDF scales only up to that level's proportion. Summed across levels, the maximum is 1. Optionally, posterior and/or prior predictive CDFs can be overlaid.

Usage

plot_cdf(
  input,
  post_predict = NULL,
  prior_predict = NULL,
  subject = NULL,
  quants = c(0.025, 0.975),
  functions = NULL,
  factors = NULL,
  defective_factor = "R",
  n_cores = 1,
  n_post = 50,
  layout = NA,
  to_plot = c("data", "posterior", "prior")[1:2],
  use_lim = c("data", "posterior", "prior")[1:2],
  legendpos = c("top", "topright"),
  posterior_args = list(),
  prior_args = list(),
  ...
)

Arguments

input

Either an emc object or a data frame, or a list of such objects.

post_predict

Optional posterior predictive data (matching columns) or list thereof.

prior_predict

Optional prior predictive data (matching columns) or list thereof.

subject

Subset the data to a single subject (by index or name).

quants

Numeric vector of credible interval bounds (e.g. c(0.025, 0.975)).

functions

A function (or list of functions) that create new columns in the datasets or predictives

factors

Character vector of factor names to aggregate over; defaults to plotting full data set ungrouped by factors if NULL.

defective_factor

Name of the factor used for the defective CDF (default "R").

n_cores

Number of CPU cores to use if generating predictives from an emc object.

n_post

Number of posterior draws to simulate if needed for predictives.

layout

Numeric vector used in par(mfrow=...); use NA for auto-layout.

to_plot

Character vector: any of "data", "posterior", "prior".

use_lim

Character vector controlling which source(s) define xlim.

legendpos

Character vector controlling the positions of the legends

posterior_args

Optional list of graphical parameters for posterior lines/ribbons.

prior_args

Optional list of graphical parameters for prior lines/ribbons.

...

Other graphical parameters for the real data lines.

Value

Returns NULL invisibly.

Examples

# Plot defective CDF for data only
# plot_cdf(forstmann, to_plot = "data")
#
# Plot with posterior predictions
# plot_cdf(samples_LNR, to_plot = c("data","posterior"), n_post=10)
#
# Or a list of multiple emc objects ...