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Relevant bibliographies by topics / Ratio-of-uniforms method

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Academic literature on the topic 'Ratio-of-uniforms method'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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Journal articles on the topic "Ratio-of-uniforms method"

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Leydold, Josef. "Automatic sampling with the ratio-of-uniforms method." ACM Transactions on Mathematical Software 26, no. 1 (2000): 78–98. http://dx.doi.org/10.1145/347837.347863.

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Leydold, Josef. "Short universal generators via generalized ratio-of-uniforms method." Mathematics of Computation 72, no. 243 (2003): 1453–72. http://dx.doi.org/10.1090/s0025-5718-03-01511-4.

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Young, Dean M., John W. Seaman, and Danny W. Turner. "A ratio-of-uniforms method for generating exponential power variates." Journal of Statistical Computation and Simulation 35, no. 1-2 (1990): 13–18. http://dx.doi.org/10.1080/00949659008811231.

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Wakefield, J. C., A. E. Gelfand, and A. F. M. Smith. "Efficient generation of random variates via the ratio-of-uniforms method." Statistics and Computing 1, no. 2 (1991): 129–33. http://dx.doi.org/10.1007/bf01889987.

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Wang, Min, Xiaoqian Sun, and Chanseok Park. "Bayesian analysis of Birnbaum–Saunders distribution via the generalized ratio-of-uniforms method." Computational Statistics 31, no. 1 (2015): 207–25. http://dx.doi.org/10.1007/s00180-015-0629-z.

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ormann, Wolfgang, and Gerhard erflinger. "The transformed rejection method for generating random variables, an alternative to the ratio of uniforms method." Communications in Statistics - Simulation and Computation 23, no. 3 (1994): 847–60. http://dx.doi.org/10.1080/03610919408813203.

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Pérez, C. J., J. Martín, C. Rojano, and F. J. Girón. "Efficient generation of random vectors by using the ratio-of-uniforms method with ellipsoidal envelopes." Statistics and Computing 18, no. 2 (2008): 209–17. http://dx.doi.org/10.1007/s11222-007-9049-4.

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Hörmann, Wolfgang. "A note on the quality of random variates generated by the ratio of uniforms method." ACM Transactions on Modeling and Computer Simulation 4, no. 1 (1994): 96–106. http://dx.doi.org/10.1145/174619.174623.

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Popescu, Ileana, and Monica Dumitrescu. "Laha Distribution: Computer Generation and Applications to Life Time Modelling." JUCS - Journal of Universal Computer Science 5, no. (8) (1999): 471–81. https://doi.org/10.3217/jucs-005-08-0471.

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Laha distribution has been introduced in 1958 as an example of a non-normal distribution where the quotient follows the Cauchy law. In this paper we present two procedures for the computer generation of this distribution and we discuss its applications to life time modelling.

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Liu, Yang, and Balgobin Nandram. "Sampling methods for the concentration parameter and discrete baseline of the Dirichlet Process." Statistics in Transition New Series 23, no. 4 (2022): 21–36. http://dx.doi.org/10.2478/stattrans-2022-0040.

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Abstract There are many models in the current statistical literature for making inferences based on samples selected from a finite population. Parametric models may be problematic because statistical inference is sensitive to parametric assumptions. The Dirichlet process (DP) prior is very flexible and determines the complexity of the model. It is indexed by two hyper-parameters: the baseline distribution and concentration parameter. We address two distinct problems in the article. Firstly, we review the current sampling methods for the concentration parameter, which use the continuous baselin

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Dissertations / Theses on the topic "Ratio-of-uniforms method"

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Leydold, Josef. "Automatic Sampling with the Ratio-of-uniforms Method." Department of Statistics and Mathematics, Abt. f. Angewandte Statistik u. Datenverarbeitung, WU Vienna University of Economics and Business, 1999. http://epub.wu.ac.at/84/1/document.pdf.

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Applying the ratio-of-uniforms method for generating random variates results in very efficient, fast and easy to implement algorithms. However parameters for every particular type of density must be precalculated analytically. In this paper we show, that the ratio-of-uniforms method is also useful for the design of a black-box algorithm suitable for a large class of distributions, including all with log-concave densities. Using polygonal envelopes and squeezes results in an algorithm that is extremely fast. In opposition to any other ratio-of-uniforms algorithm the expected number of uniform r

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Leydold, Josef. "Short Universal Generators Via Generalized Ratio-of-Uniforms Method." Department of Statistics and Mathematics, Abt. f. Angewandte Statistik u. Datenverarbeitung, WU Vienna University of Economics and Business, 2000. http://epub.wu.ac.at/348/1/document.pdf.

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We use inequalities to design short universal algorithms that can be used to generate random variates from large classes of univariate continuous or discrete distributions (including all log-concave distributions). The expected time is uniformly bounded over all these distributions for a particular generator. The algorithms can be implemented in a few lines of high level language code. (author's abstract)<br>Series: Preprint Series / Department of Applied Statistics and Data Processing

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Hörmann, Wolfgang, and Gerhard Derflinger. "The Transformed Rejection Method for Generation Random Variables, an Alternative to the Ratio of Uniforms Method." Department of Statistics and Mathematics, Abt. f. Angewandte Statistik u. Datenverarbeitung, WU Vienna University of Economics and Business, 1994. http://epub.wu.ac.at/1314/1/document.pdf.

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Theoretical considerations and empirical results show that the one-dimensional quality of non-uniform random numbers is bad and the discrepancy is high when they are generated by the ratio of uniforms method combined with linear congruential generators. This observation motivates the suggestion to replace the ratio of uniforms method by transformed rejection (also called exact approximation or almost exact inversion), as the above problem does not occur for this method. Using the function $G(x) =\left( \frac(a)(1-x)+b\right)x $ with appropriate $a$ and $b$ as approximation of the inverse distr

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Hörmann, Wolfgang. "A note on the quality of random variates generated by the ratio of uniforms method." Institut für Statistik und Mathematik, Abt. f. Angewandte Statistik u. Datenverarbeitung, WU Vienna University of Economics and Business, 1993. http://epub.wu.ac.at/1440/1/document.pdf.

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The one-dimensional distribution of pseudo-random numbers generated by the ratio of uniforms methods using linear congruential generators (LCGs) as the source of uniform random numbers is investigated in this paper. Due to the two-dimensional lattice structure of LCGs there is always a comparable large gap without a point in the one-dimensional distribution of any ratio of uniforms method. Lower bounds for these probabilities only depending on the modulus and the Beyer quotient of the LCG are proved for the case that the Cauchy the normal or the exponential distribution are generated. These bo

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Leydold, Josef, and Wolfgang Hörmann. "Universal Algorithms as an Alternative for Generating Non-Uniform Continuous Random Variates." Department of Statistics and Mathematics, Abt. f. Angewandte Statistik u. Datenverarbeitung, WU Vienna University of Economics and Business, 2000. http://epub.wu.ac.at/844/1/document.pdf.

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This paper presents an overview of the most powerful universal methods. These are based on acceptance/rejection techniques where hat and squeezes are constructed automatically. Although originally motivated to sample from non-standard distributions these methods have advantages that make them attractive even for sampling from standard distributions and thus are an alternative to special generators tailored for particular distributions. Most important are: the marginal generation time is fast and does not depend on the distribution. They can be used for variance reduction techniques, and they p

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Karawatzki, Roman, Josef Leydold, and Klaus Pötzelberger. "Automatic Markov Chain Monte Carlo Procedures for Sampling from Multivariate Distributions." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 2005. http://epub.wu.ac.at/1400/1/document.pdf.

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Generating samples from multivariate distributions efficiently is an important task in Monte Carlo integration and many other stochastic simulation problems. Markov chain Monte Carlo has been shown to be very efficient compared to "conventional methods", especially when many dimensions are involved. In this article we propose a Hit-and-Run sampler in combination with the Ratio-of-Uniforms method. We show that it is well suited for an algorithm to generate points from quite arbitrary distributions, which include all log-concave distributions. The algorithm works automatically in the sense that

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Leydold, Josef. "A Simple Universal Generator for Continuous and Discrete Univariate T-concave Distributions." Department of Statistics and Mathematics, Abt. f. Angewandte Statistik u. Datenverarbeitung, WU Vienna University of Economics and Business, 2000. http://epub.wu.ac.at/1756/1/document.pdf.

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We use inequalities to design short universal algorithms that can be used to generate random variates from large classes of univariate continuous or discrete distributions (including all log-concave distributions). The expected time is uniformly bounded over all these distributions. The algorithms can be implemented in a few lines of high level language code. In opposition to other black-box algorithms hardly any setup step is required and thus it is superior in the changing parameter case. (author's abstract)<br>Series: Preprint Series / Department of Applied Statistics and Data Processing

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"Automatic Sampling with the Ratio-of-uniforms Method." Department of Statistics and Mathematics, Abt. f. Angewandte Statistik u. Datenverarbeitung, 1999. http://epub.wu-wien.ac.at/dyn/dl/wp/epub-wu-01_9e0.

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"Short Universal Generators Via Generalized Ratio-of-Uniforms Method." Department of Statistics and Mathematics, Abt. f. Angewandte Statistik u. Datenverarbeitung, 2000. http://epub.wu-wien.ac.at/dyn/dl/wp/epub-wu-01_9e7.

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Groendyke, Christophe. "Ratio-of-uniforms Markov chain Monte Carlo for Gaussian process models." 2008. http://etda.libraries.psu.edu/theses/approved/WorldWideIndex/ETD-2683/index.html.

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Book chapters on the topic "Ratio-of-uniforms method"

1

Martino, Luca, David Luengo, and Joaquín Míguez. "Ratio of Uniforms." In Independent Random Sampling Methods. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-72634-2_5.

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Conference papers on the topic "Ratio-of-uniforms method"

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Stadlober, E. "Ratio of uniforms as a convenient method for sampling from classical discrete distributions." In the 21st conference. ACM Press, 1989. http://dx.doi.org/10.1145/76738.76801.

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