Access the full text.
Sign up today, get DeepDyve free for 14 days.
References for this paper are not available at this time. We will be adding them shortly, thank you for your patience.
Three algorithms for sampling from exponential, Cauchy and normal distributions are developed. They are based on the "exact approximation" method, and their expected numbers of consumed uniform deviates are less than 1.04 per sample from the target distributions. The algorithms are simple and easily implemented in any desired precision. They require no space for long tables of auxiliary vectors, merely a few constants are needed. Nevertheless, their speed compares well with the performance of much more complex and table-aided sampling procedures.
Communications of the ACM – Association for Computing Machinery
Published: Nov 1, 1988
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.