exponential_distribution: Exponential Distribution Functions

In boostmath: 'R' Bindings for the 'Boost' Math Functions

Exponential Distribution Functions

Description

Functions to compute the probability density function, cumulative distribution function, and quantile function for the Exponential distribution.

Usage

exponential_distribution(lambda = 1)

exponential_pdf(x, lambda = 1)

exponential_lpdf(x, lambda = 1)

exponential_cdf(x, lambda = 1)

exponential_lcdf(x, lambda = 1)

exponential_quantile(p, lambda = 1)

Arguments

lambda	rate parameter (lambda > 0)
x	quantile
p	probability (0 <= p <= 1)

Value

A single numeric value with the computed probability density, log-probability density, cumulative distribution, log-cumulative distribution, or quantile depending on the function called.

See Also

Boost Documentation for more details on the mathematical background.

Examples

# Exponential distribution with rate parameter lambda = 2
dist <- exponential_distribution(2)
# Apply generic functions
cdf(dist, 0.5)
logcdf(dist, 0.5)
pdf(dist, 0.5)
logpdf(dist, 0.5)
hazard(dist, 0.5)
chf(dist, 0.5)
mean(dist)
median(dist)
mode(dist)
range(dist)
quantile(dist, 0.2)
standard_deviation(dist)
support(dist)
variance(dist)
skewness(dist)
kurtosis(dist)
kurtosis_excess(dist)

# Convenience functions
exponential_pdf(1, 2)
exponential_lpdf(1, 2)
exponential_cdf(1, 2)
exponential_lcdf(1, 2)
exponential_quantile(0.5, 2)

boostmath documentation built on Dec. 15, 2025, 5:07 p.m.