This function generates a cumulative interval plot based on the provided lower and upper bounds, cluster IDs, and other optional parameters.
Usage
plot_intervals_cumulative(
lower,
upper,
cluster_id,
truth = NA,
min,
max,
facet_wrap = NULL,
weighted = NULL,
show_quantiles = TRUE,
ncol = 3
)Arguments
- lower
A numeric vector of lower bounds.
- upper
A numeric vector of upper bounds.
- cluster_id
A vector of cluster IDs corresponding to the intervals.
- truth
A numeric vector of ground truth values. Default is NA.
- min
The minimum value for the x-axis.
- max
The maximum value for the x-axis.
- facet_wrap
A logical value indicating whether to use facet wrapping. Default is NULL.
- weighted
An optional vector of weights for the intervals.
- show_quantiles
A logical value indicating whether to show quantiles on the plot. Default is TRUE.
- ncol
The number of columns for facet wrapping. Default is 3.
Examples
# Example data
lower_bounds <- c(0.01, 0.3, 0.02, 0.4)
upper_bounds <- c(0.5, 0.96, 0.6, 0.8)
cluster_ids <- c(1, 1, 2, 2)
truth_values <- c(0.3, 0.3, 0.6, 0.6)
# Create cumulative interval plot
plot_intervals_cumulative(
lower = lower_bounds,
upper = upper_bounds,
cluster_id = cluster_ids,
truth = truth_values,
min = 0,
max = 1,
weighted = FALSE
)
#> Joining with `by = join_by(cluster_id)`
