arXiv:1307.1223math.NA
Fast inverse transform sampling in one and two dimensions
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Abstract
We develop a computationally efficient and robust algorithm for generating pseudo-random samples from a broad class of smooth probability distributions in one and two dimensions. The algorithm is based on inverse transform sampling with a polynomial approximation scheme using Chebyshev polynomials, Chebyshev grids, and low rank function approximation. Numerical experiments demonstrate that our algorithm outperforms existing approaches.
Here’s a really neat new approach, Olver & Townsend, “Fast inverse transform sampling in one and two dimensions” http://arxiv.org/pdf/1307.1223v1.pdf Built on top of Chebfun, http://www.chebfun.org
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