plot_stat: Plot Statistics on Data

In EMC2: Bayesian Hierarchical Analysis of Cognitive Models of Choice

Plot Statistics on Data

Description

Plots panels that contain a set of densities for each level of the specified factor The densities represent the predicted data across the posterior, the vertical lines represent the real data.

Usage

plot_stat(
  input,
  post_predict = NULL,
  prior_predict = NULL,
  stat_fun,
  stat_name = NULL,
  subject = NULL,
  factors = NULL,
  n_cores = 1,
  n_post = 50,
  quants = c(0.025, 0.5, 0.975),
  functions = NULL,
  layout = NA,
  to_plot = c("data", "posterior", "prior")[1:2],
  use_lim = c("data", "posterior", "prior")[1:2],
  legendpos = c("topleft", "top"),
  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.
stat_fun	A function that can be applied to the data and returns a single value or a vector of values.
stat_name	The name of the calculated quantity
subject	Subset the data to a single subject (by index or name).
factors	Character vector of factor names to aggregate over; defaults to plotting full data set ungrouped by factors if NULL.
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.
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
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

an invisible data frame with the stat applied to the real data, posterior predictives and/or prior predictives

Examples

# For example plot the observed and predicted response accuracy
# Can also apply more sophisticated statistics
drt <- function(data) diff(tapply(data$rt,data[,c("E")],mean))
plot_stat(samples_LNR, stat_fun = drt, n_post = 10, stat_name = "RT diff Speed - A/N")

EMC2 documentation built on April 11, 2025, 5:50 p.m.