Generate Random Inverse Gaussian in R

[This article was first published on Lindons Log » R, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Needed to generate draws from an inverse Gaussian today, so I wrote the following Rcpp code:

#include <RcppArmadillo.h>
// [[Rcpp::depends(RcppArmadillo)]]

using namespace Rcpp;
using namespace arma;

// [[Rcpp::export]]
Col<double> rrinvgauss(int n, double mu, double lambda){

	Col<double> random_vector(n);
	double z,y,x,u;

	for(int i=0; i<n; ++i){
		z=R::rnorm(0,1);
		y=z*z;
		x=mu+0.5*mu*mu*y/lambda - 0.5*(mu/lambda)*sqrt(4*mu*lambda*y+mu*mu*y*y);
		u=R::runif(0,1);
		if(u <= mu/(mu+x)){
			random_vector(i)=x;
		}else{
			random_vector(i)=mu*mu/x;
		};
	}
	return(random_vector);
}

It seems to be faster than existing implementations such as rig from mgcv and rinvgauss from statmod packages.

library(Rcpp) 
library(RcppArmadillo)
library(rbenchmark)
library(statmod)
library(mgcv)
sourceCpp("rrinvgauss.cpp")
n=10000 
benchmark(rig(n,1,1),rinvgauss(n,1,1),rrinvgauss(n,1,1),replications=100)

inverse gaussian

rename rrinvgauss as desired.

The post Generate Random Inverse Gaussian in R appeared first on Lindons Log.

To leave a comment for the author, please follow the link and comment on their blog: Lindons Log » R.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)