beta_functions: Beta Functions

beta_functionsR Documentation

Beta Functions

Description

Functions to compute the Euler beta function, normalised incomplete beta function, and their complements, as well as their inverses and derivatives.

Usage

beta_boost(a, b, x = NULL)

ibeta(a, b, x)

ibetac(a, b, x)

betac(a, b, x)

ibeta_inv(a, b, p)

ibetac_inv(a, b, q)

ibeta_inva(b, x, p)

ibetac_inva(b, x, q)

ibeta_invb(a, x, p)

ibetac_invb(a, x, q)

ibeta_derivative(a, b, x)

Arguments

a

First parameter of the beta function

b

Second parameter of the beta function

x

Upper limit of integration (0 <= x <= 1)

p

Probability value (0 <= p <= 1)

q

Probability value (0 <= q <= 1)

Value

A single numeric value with the computed beta function, normalised incomplete beta function, or their complements, depending on the function called.

See Also

Boost Documentation for more details on the mathematical background.

Examples

## Not run: 
# Euler beta function B(2, 3)
beta_boost(2, 3)
# Normalised incomplete beta function I_x(2, 3) for x = 0.5
ibeta(2, 3, 0.5)
# Normalised complement of the incomplete beta function 1 - I_x(2, 3) for x = 0.5
ibetac(2, 3, 0.5)
# Full incomplete beta function B_x(2, 3) for x = 0.5
beta_boost(2, 3, 0.5)
# Full complement of the incomplete beta function 1 - B_x(2, 3) for x = 0.5
betac(2, 3, 0.5)
# Inverse of the normalised incomplete beta function I_x(2, 3) = 0.5
ibeta_inv(2, 3, 0.5)
# Inverse of the normalised complement of the incomplete beta function I_x(2, 3) = 0.5
ibetac_inv(2, 3, 0.5)
# Inverse of the normalised complement of the incomplete beta function I_x(a, b)
# with respect to a for x = 0.5 and q = 0.5
ibetac_inva(3, 0.5, 0.5)
# Inverse of the normalised incomplete beta function I_x(a, b)
# with respect to b for x = 0.5 and p = 0.5
ibeta_invb(0.8, 0.5, 0.5)
# Inverse of the normalised complement of the incomplete beta function I_x(a, b)
# with respect to b for x = 0.5 and q = 0.5
ibetac_invb(2, 0.5, 0.5)
# Derivative of the incomplete beta function with respect to x for a = 2, b = 3, x = 0.5
ibeta_derivative(2, 3, 0.5)

## End(Not run)

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