Awesome

eigenmvn

Multivariate Normal distribution sampling using C++11 and Eigen matrices.

This is taken from http://stackoverflow.com/questions/16361226/error-while-creating-object-from-templated-class (also see http://lost-found-wandering.blogspot.fr/2011/05/sampling-from-multivariate-normal-in-c.html)

I have been unable to contact the original author, and I've performed the following modifications to the original code:

• removal of the dependency to Boost, in favor of straight C++11;

• ability to choose from Solver or Cholesky decomposition (supposedly faster);

• fixed Cholesky by using LLT decomposition instead of LDLT that was not yielding a correctly rotated variance. See this link for more details: http://stats.stackexchange.com/questions/48749/how-to-sample-from-a-multivariate-normal-given-the-pt-ldlt-p-decomposition-o

• turned matrix fixed sizes into dynamic sizes.

Usage

Compile the test exe with

g++ -I/usr/include -I/usr/include/eigen3 -g -std=c++11 test_eigenmvn.cc -o te

run with

./te

Look at results with gnuplot:

gnuplot
plot 'samples_solver.txt', 'samples_cholesky.txt'