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Journal ArticleDOI

An Efficient Method for Generating Discrete Random Variables with General Distributions

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TLDR
The fast generation of discrete random variables with arbitrary frequency distributions is discussed, related to rejection techniques but differs from them in that all samples comprising the input data contribute to the samples in the target distribution.
Abstract
The fast generation of discrete random variables with arbitrary frequency distributions is discussed. The proposed method is related to rejection techniques but differs from them in that all samples comprising the input data contribute to the samples in the target distribution. The software implementation of the method requires at most two memory references and a comparison. The method features good accuracy and modest storage requirements. I t is particularly useful in small computers with limited memory capacity.

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Citations
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Journal ArticleDOI

A linear algorithm for generating random numbers with a given distribution

TL;DR: Improvements to a fast method of generating sample values for xi in constant time are suggested, which reduces the time required for initialization to O(n).
Patent

Gaming machine having truly random results

TL;DR: In this paper, a game machine produces truly random results using a noisy oscillator to randomly vary the frequency of a clock signal used to cycle a counter through its states, and multiple random numbers can be generated during the same game using the same circuitry.
Posted Content

Monte Carlo simulation and numerical integration

TL;DR: A survey of simulation methods in economics, with a specific focus on integration problems, is presented in this paper, where acceptance methods, importance sampling procedures, and Markov chain Monte Carlo methods for simulation from univariate and multivariate distributions and their application to the approximation of integrals.
Journal ArticleDOI

Gaussian random number generators

TL;DR: The algorithms underlying various GRNGs are described, their computational requirements are compared, and the quality of the random numbers are examined with emphasis on the behaviour in the tail region of the Gaussian probability density function.
Book

Numerical Methods Of Statistics

TL;DR: This book explains how computer software is designed to perform the tasks required for sophisticated statistical analysis and treats the application of numerical tools; numerical integration and random number generation are explained in a unified manner reflecting complementary views of Monte Carlo methods.
References
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Journal ArticleDOI

An approximate method for generating asymmetric random variables

TL;DR: A method for generating values of continuous symmetric random variables that is relatively fast, requires essentially no computer memory, and is easy to use is developed.
Journal ArticleDOI

New fast method for generating discrete random numbers with arbitrary frequency distributions

TL;DR: A new method for generating discrete random numbers with arbitrary amplitude/frequency distributions is presented, which consists essentially of amplitude manipulation of uniformly distributed, statistically independent sequential numbers.
Journal ArticleDOI

Fast generation of uniformly distributed pseudorandom numbers with floating-point representation

TL;DR: A new method is presented for generating uniformly distributed pesudorandom numbers with a floating-point representation that features fast single-clock-pulse operation.
Journal ArticleDOI

Pseudonoise with Arbitrary Amplitude Distribution--Part I: Theory

TL;DR: A new sampling method, conditional bit sampling, which is suited for hardwired sampling devices because of its generality, simplicity, and accuracy, and agreement between actual and theoretical performance was excellent.