Model Agnostic Prediction Intervals

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Documentation for package ‘pintervals’ version 1.0.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

Help Pages

abs_error	Absolute Error Function for Non-Conformity Scores
bcss_compute	Function to compute the between-cluster sum of squares (BCSS) for a set of clusters
bindividual_alpha	Bin-individual alpha function for conformal prediction
bin_chopper	Bin chopper function for binned bootstrapping
bootstrap_inner	Bootstrap function for bootstrapping the prediction intervals
cauchy_kern	Cauchy Kernel Function
ch_index	Function to compute the Calinski-Harabasz index for a set of clusters
class_to_clusters	Function to convert class vector to cluster vector based on calibrated clusters
clusterer	Function to cluster non-conformity scores using either Kolmogorov-Smirnov or K-means clustering
contiguize_intervals	Contiguize non-contiguous intervals
county_turnout	U.S. county-level turnout and demographic context (MIT Election Lab 2018 Election Analysis Dataset + additions)
coverage_gap_finder	Function to find the coverage gap for a set of clusters
Dm_finder	Function to find the minimum distance between a class and a set of clusters
dm_to_prob	Function to convert distance measure to probability
elections	Election-year democracy indicators from V-Dem (1946–2024)
flatten_cp_bin_intervals	Flatten binned conformal prediction intervals to contiguous intervals
gauss_kern	Gaussian Kernel Function
grid_finder	Grid search for lower and upper bounds of continuous conformal prediction intervals
grid_inner	Inner function for grid search
heterogeneous_error	Heterogeneous Error Function for Non-Conformity Scores
interval_coverage	Empirical coverage of prediction intervals
interval_miscoverage	Empirical miscoverage of prediction intervals
interval_score	Mean interval score (MIS) for prediction intervals
interval_width	Mean width of prediction intervals
kmeans_cluster_qecdf	Function to perform K-means clustering on quantile empirical cumulative distribution functions (qECDFs) of non-conformity scores
ks_cluster	Function to perform Kolmogorov-Smirnov clustering on non-conformity scores
ks_cluster_assignment_step	Function to assign classes to clusters based on Kolmogorov-Smirnov clustering
ks_cluster_init_step	Function to initialize clusters for Kolmogorov-Smirnov clustering
logistic_kern	Logistic Kernel Function
minq_to_alpha	Helper for minimum quantile to alpha function
ncs_compute	Non-Conformity Score Computation Function
optimize_clusters	Function to optimize clusters based on the Calinski-Harabasz index
pinterval_bccp	Bin-conditional conformal prediction intervals for continuous predictions
pinterval_bootstrap	Bootstrap prediction intervals
pinterval_ccp	Clustered conformal prediction intervals for continuous predictions
pinterval_conformal	Conformal Prediction Intervals of Continuous Values
pinterval_mondrian	Mondrian conformal prediction intervals for continuous predictions
pinterval_parametric	#' Parametric prediction intervals for continuous predictions
raw_error	Raw Error Function for Non-Conformity Scores
reciprocal_linear_kern	Reciprocal Linear Kernel Function
rel_error	Relative Error Function for Non-Conformity Scores by predicted Values
wcss_compute	Function to compute the within-cluster sum of squares (WCSS) for a set of clusters
za_rel_error	Zero-adjusted Relative Error Function for Non-Conformity Scores by predicted Values with a small adjustment