Compares the p-value/s-value, and likelihood functions and computes an AUC number.
curve_compare(data1, data2, type = "c", plot = TRUE, ...)The first dataframe produced by one of the interval functions in which the intervals are stored.
The second dataframe produced by one of the interval functions in which the intervals are stored.
Choose whether to plot a "consonance" function, a "surprisal" function or "likelihood". The default option is set to "c". The type must be set in quotes, for example curve_compare (type = "s") or curve_compare(type = "c"). Other options include "pd" for the consonance distribution function, and "cd" for the consonance density function, "l1" for relative likelihood, "l2" for log-likelihood, "l3" for likelihood and "d" for deviance function.
by default it is set to TRUE and will use the plot_compare() function to plot the two functions.
Can be used to pass further arguments to plot_compare().
Computes an AUC score and returns a plot that graphs two functions.
if (FALSE) { # \dontrun{
library(concurve)
GroupA <- rnorm(50)
GroupB <- rnorm(50)
RandomData <- data.frame(GroupA, GroupB)
intervalsdf <- curve_mean(GroupA, GroupB, data = RandomData)
GroupA2 <- rnorm(50)
GroupB2 <- rnorm(50)
RandomData2 <- data.frame(GroupA2, GroupB2)
model <- lm(GroupA2 ~ GroupB2, data = RandomData2)
randomframe <- curve_gen(model, "GroupB2")
curve_compare(intervalsdf[[1]], randomframe[[1]])
} # }