jsd_continuous: Estimate JSD for continuous variables

In jsdtools: Jensen-Shannon Divergence Estimation, Confidence Intervals, and Distribution Plots

Estimate JSD for continuous variables

Description

Computes Jensen-Shannon divergence (JSD) between two numeric vectors using kernel density estimation (KDE) and numerical integration.

Usage

jsd_continuous(
  x,
  y,
  L = NULL,
  U = NULL,
  base = 2,
  bw = "nrd0",
  kernel = "gaussian",
  grid_n = 4096,
  qrange = c(0.001, 0.999),
  extend = 3,
  eps = 1e-12,
  renormalize = TRUE,
  na_rm = TRUE
)

Arguments

x	Numeric vector for group 1.
y	Numeric vector for group 2.
L	Optional lower integration bound.
U	Optional upper integration bound.
base	Logarithm base. Defaults to 2. Use 'exp(1)' for nats.
bw	Bandwidth passed to [stats::density()].
kernel	Kernel passed to [stats::density()].
grid_n	Number of grid points used for KDE.
qrange	Quantile range used when 'L' and 'U' are not supplied.
extend	Extension multiplier for the automatically chosen range.
eps	Small constant for numerical stability.
renormalize	Logical; renormalize estimated densities over the grid?
na_rm	Logical; remove missing values?

Value

An object of class '"jsd_estimate"'.

jsdtools documentation built on March 31, 2026, 1:06 a.m.