rinvgaussian: Sample from inverse Gaussian

In pierrejacob/debiasedmcmc: Unbiased MCMC with couplings

Sample from inverse Gaussian

Description

Parametrized by mu, lambda, with log-density given by

0.5 * log(λ/(2*π)) - 1.5 * log(x) - λ * (x-μ)^2 / (2 * μ^2 * x)

The procedure goes as follows.

• Generate nu ~ Normal(0,1).

• Define y = nu^2.

• Define x = mu + mu^2 * y / (2 * lambda) - mu / (2 * lambda) * sqrt(4 * mu * lambda * y + mu^2 * y^2).

• Generate Z ~ Uniform(0,1).

• If z <= mu / (mu + x), output x, otherwise output mu^2 / x.

Usage

rinvgaussian(n, mu, lambda)

Value

A vector of n draws, where n is the first argument.

pierrejacob/debiasedmcmc documentation built on Aug. 22, 2022, 12:41 a.m.