Journal ArticleDOI
An Efficient Method for Generating Discrete Random Variables with General Distributions
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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.read more
Citations
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Journal ArticleDOI
On Mixture Methods for the Computer Generation of Random Variables
TL;DR: It is shown that several of the general tools commonly used in generating random variables can be described as mixture methods, and a variation of the acceptance-rejection method that avoids repetition of steps is illustrated.
Journal ArticleDOI
Counting and Sampling Markov Equivalent Directed Acyclic Graphs
Topi Talvitie,Mikko Koivisto +1 more
TL;DR: This work considers counting and uniform sampling of DAGs that are Markov equivalent to a given DAG, and gives two algorithms that enable uniform sampling from the equivalence class at a computational cost linear in the graph size.
Proceedings ArticleDOI
Memory-Aware Framework for Efficient Second-Order Random Walk on Large Graphs
TL;DR: A cost model is designed, and a new node sampling method following the acceptance-rejection paradigm is proposed to achieve a better balance between memory and time cost and a memory-aware framework is proposed on the basis of the cost model.
Journal ArticleDOI
Monte Carlo estimation of the maximal flow distribution with discrete stochastic arc capacity levels
Book ChapterDOI
Perfect sampling of networks with finite and infinite capacity queues
TL;DR: It is shown that perfect sampling is possible, although the underlying Markov chain has a large or even infinite state space, and a Jackson network with infinite buffers is used to bound the number of initial conditions to be considered in the coupling from the past scheme.
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
John S. Sobolewski,W. H. Payne +1 more
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.