plot_pit | R Documentation |
Make a simple histogram of the probability integral transformed values to visually check whether a uniform distribution seems likely.
plot_pit(pit, num_bins = "auto", breaks = NULL)
pit |
either a vector with the PIT values of size n, or a data.frame as
produced by |
num_bins |
the number of bins in the PIT histogram, default is "auto".
When |
breaks |
numeric vector with the break points for the bins in the
PIT histogram. This is preferred when creating a PIT histogram based on
quantile-based data. Default is |
vector with the scoring values
data.table::setDTthreads(1) # only needed to avoid issues on CRAN # PIT histogram in vector based format true_values <- rnorm(30, mean = 1:30) predictions <- replicate(200, rnorm(n = 30, mean = 1:30)) pit <- pit_sample(true_values, predictions) plot_pit(pit) # quantile-based pit pit <- pit(example_quantile, by = c("model")) plot_pit(pit, breaks = seq(0.1, 1, 0.1)) # sample-based pit pit <- pit(example_integer, by = c("model")) plot_pit(pit)
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