Smoothed Transformed Density Rejection

Leydold, Josef and Hörmann, Wolfgang (2003) Smoothed Transformed Density Rejection. Preprint Series / Department of Applied Statistics and Data Processing, 51. Department of Statistics and Mathematics, Abt. f. Angewandte Statistik u. Datenverarbeitung, WU Vienna University of Economics and Business, Vienna.


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There are situations in the framework of quasi-Monte Carlo integration where nonuniform low-discrepancy sequences are required. Using the inversion method for this task usually results in the best performance in terms of the integration errors. However, this method requires a fast algorithm for evaluating the inverse of the cumulative distribution function which is often not available. Then a smoothed version of transformed density rejection is a good alternative as it is a fast method and its speed hardly depends on the distribution. It can easily be adjusted such that it is almost as good as the inversion method. For importance sampling it is even better to use the hat distribution as importance distribution directly. Then the resulting algorithm is as good as using the inversion method for the original importance distribution but its generation time is much shorter.

Item Type: Paper
Additional Information: published in: Monte Carlo Methods and Applications 10(3-4), pp. 393-402, 2004
Keywords: Monte Carlo method / quasi-Monte Carlo method /nonuniform random variate generation / transformed density rejection / smoothed rejection / inversion
Classification Codes: MSC 65C05, 65C10, 65D30
Divisions: Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Depositing User: Repository Administrator
Date Deposited: 10 Jul 2006 13:41
Last Modified: 22 Oct 2019 00:41


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