Package index • kldest

All functions

combinations(): Combinations of input arguments

constDiagMatrix(): Constant plus diagonal matrix

convergence_rate(): Empirical convergence rate of a KL divergence estimator

is_two_sample(): Detect if a one- or two-sample problem is specified

kld_ci_bootstrap(): Uncertainty of KL divergence estimate using Efron's bootstrap.

kld_ci_subsampling(): Uncertainty of KL divergence estimate using Politis/Romano's subsampling bootstrap.

kld_discrete(): Analytical KL divergence for two discrete distributions

kld_est(): Kullback-Leibler divergence estimator for discrete, continuous or mixed data.

kld_est_brnn(): Bias-reduced generalized k-nearest-neighbour KL divergence estimation

kld_est_discrete(): Plug-in KL divergence estimator for samples from discrete distributions

kld_est_kde(): Kernel density-based Kullback-Leibler divergence estimation in any dimension

kld_est_kde1(): 1-D kernel density-based estimation of Kullback-Leibler divergence

kld_est_kde2(): 2-D kernel density-based estimation of Kullback-Leibler divergence

kld_est_neural(): Neural KL divergence estimation (Donsker-Varadhan representation) using torch

kld_est_nn(): k-nearest neighbour KL divergence estimator

kld_exponential(): Analytical KL divergence for two univariate exponential distributions

kld_gaussian(): Analytical KL divergence for two uni- or multivariate Gaussian distributions

kld_uniform(): Analytical KL divergence for two uniform distributions

kld_uniform_gaussian(): Analytical KL divergence between a uniform and a Gaussian distribution

mvdnorm(): Probability density function of multivariate Gaussian distribution

to_uniform_scale(): Transform samples to uniform scale

tr(): Matrix trace operator

trapz(): Trapezoidal integration in 1 or 2 dimensions