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http://dx.doi.org/10.7465/jkdi.2015.26.3.593

Performance comparison of random number generators based on Adaptive Rejection Sampling  

Kim, Hyotae (Department of Statistics, Korea University)
Jo, Seongil (Department of Statistics, Korea University)
Choi, Taeryon (Department of Statistics, Korea University)
Publication Information
Journal of the Korean Data and Information Science Society / v.26, no.3, 2015 , pp. 593-610 More about this Journal
Abstract
Adaptive Rejection Sampling (ARS) method is a well-known random number generator to acquire a random sample from a probability distribution, and has the advantage of improving the proposal distribution during the sampling procedures, which update it closer to the target distribution. However, the use of ARS is limited since it can be used only for the target distribution in the form of the log-concave function, and thus various methods have been proposed to overcome such a limitation of ARS. In this paper, we attempt to compare five random number generators based on ARS in terms of adequacy and efficiency. Based on empirical analysis using simulations, we discuss their results and make a comparison of five ARS-based methods.
Keywords
Adaptive rejection sampling; log-concave function; multi-modal function; random number generator; simulations;
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Times Cited By KSCI : 3  (Citation Analysis)
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