Year: 2013
Type: preprint
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.
Source: arXiv (Cornell University)
Authors: Olver, Sheehan, Townsend, Alex
Institutions: The University of Sydney, University of Oxford
Language: English
Subfield: Numerical Analysis
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W1580003832