plot.cafs {dRiftDM} | R Documentation |
Plot Conditional Accuracy Functions (CAFs)
Description
This function generates a plot of Conditional Accuracy Functions (CAFs). It can display observed and predicted values, making it useful for assessing model fit or exploring observed data.
Usage
## S3 method for class 'cafs'
plot(
x,
...,
conds = NULL,
col = NULL,
xlim = NULL,
ylim = c(0, 1),
xlab = "Bins",
ylab = NULL,
pch = 21,
lty = 1,
type = "l",
legend = NULL,
legend_pos = "bottomright"
)
Arguments
x |
a data.frame, containing CAFs, typically resulting from a call to calc_stats. |
... |
additional arguments passed to the plot, graphics::points, and graphics::legend functions. Oftentimes, this will (unfortunately) lead to an error due to a clash of arguments. |
conds |
character vector, specifying the conditions to plot. Defaults to all unique conditions. |
col |
Character vector, specifying colors for each condition. If a single color is provided, it will be repeated for each condition. |
xlim , ylim |
numeric vectors of length 2, specifying the x and y axis limits. |
xlab , ylab |
character, labels for the x and y axes. |
pch |
integer, specifying the plotting symbol for observed data points. |
lty |
integer, line type for the predicted CAFs. |
type |
character, type of plot for the predicted CAFs. |
legend |
character vector, specifying legend labels corresponding to the conditions in the CAFs. Defaults to the condition names. |
legend_pos |
character, specifying the position of the legend on the plot. |
Details
The plot.cafs
function allows for a quick investigation of CAFs, including
options for color, symbols, and line types for different data sources
(observed vs. predicted). When the supplied data.frame includes multiple
IDs, CAFs are aggregated across IDs before plotting.
Value
Nothing (NULL
; invisibly)
Examples
# Example 1: Only model predictions ---------------------------------------
# get a cafs data.frame for demonstration purpose
a_model <- dmc_dm(t_max = 1.5, dt = .0025, dx = .0025)
cafs <- calc_stats(a_model, type = "cafs")
# call the plot function with default values
plot(cafs)
# make the plot a little bit more pretty
plot(cafs,
col = c("green", "red"),
ylim = c(0.5, 1)
)
# Example 2: Model predictions and observed data --------------------------
obs_data(a_model) <- dmc_synth_data
cafs <- calc_stats(a_model, type = "cafs")
plot(cafs)
# Note: The model was not fitted to the data set, thus observed data and
# model predictions don't match
# Example 3: Only observed data -------------------------------------------
cafs <- calc_stats(dmc_synth_data, type = "cafs")
plot(cafs)