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2010 Winter Simulation Conference

作者： Biller, Bahar Gunes, Canan Carnegie Mellon Univ Tepper Sch Business Pittsburgh PA 15213 USA

ISBN: (纸本)9781424498642

In this tutorial we first review introductory techniques for simulation input modeling. We then identify situations in which the standard input models fail to adequately represent the available input data. In particular, we consider the cases where the input process may (i) have marginal characteristics that are not captured by standard distributions;(ii) exhibit dependence;and (iii) change over time. For case (i), we review flexible distribution systems, while we review two widely used multivariate input models for case (ii). Finally, we review nonhomogeneous Poisson processes for the last case. We focus our discussion around continuous random variables;however, when appropriate references are provided for discrete random variables. Detailed examples will be illustrated in the tutorial presentation.

关键词： Poisson distribution Poisson processes digital simulation discrete random variable random processes random variable simulation input modeling stochastic processes

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Stochastic derivation and application in information risk frequency reduction of a class of discrete random variables

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JOURNAL OF STATISTICS & MANAGEMENT SYSTEMS 2009年第1期12卷 59-64页

作者： Artikis, Panagiotis T. Artikis, Constantinos T. Agorastos, Kostas A. Vlachos, Aristidis Univ Warwick Warwick Business Sch Coventry CV4 7AL W Midlands England Univ Bradford Sch Informat Dept Comp & Math Bradford BD7 1DP W Yorkshire England Univ Macedonia Dept Business Adm Thessaloniki Greece Univ Piraeus Dept Informat GR-18534 Piraeus Greece

The class of discrete random variables taking values in the set of nonnegative integers and having probability functions with a unique mode at the point zero is generally recognized as a very strong analytical tool for stochastic modelling in many practical disciplines. The present paper establishes a stochastic derivation of this class by making use of an integral part model. Applications of the stochastic derivation in the area of risk frequency reduction operations are also provided.

关键词： discrete random variable integral part model risk frequency reduction

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An approximate method for Bayesian entropy estimation for a discrete random variable

An approximate method for Bayesian entropy estimation for a ...

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26th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society

作者： Yokota, Y Gifu Univ Fac Engn Dept Informat Sci Gifu 50111 Japan

ISBN: (纸本)0780384393

This article proposes an approximated Bayesian entropy estimator for a discrete random variable. An entropy estimator that achieves least square error is obtained through Bayesian estimation of the occurrence probabilities of each value taken by the discrete random variable. This Bayesian entropy estimator requires large amount of calculation cost if the random variable takes numerous sorts of values. Therefore, the present article proposes a practical method for calculating an Bayesian entropy estimate;the proposed method utilizes approximation of the entropy function by a truncated Taylor series. Numerical experiments demonstrate that the proposed entropy estimation method improves estimation precision of entropy remarkably in comparison to the conventional entropy estimation method.

关键词： Bayesian approach discrete random variable least square error estimation memory-less information source Shannon's entropy

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Biochemical Network Stochastic Simulator (BioNetS): software for stochastic modeling of biochemical networks

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BMC BIOINFORMATICS 2004年第1期5卷 24-24页

作者： Adalsteinsson, D McMillen, D Elston, TC Univ N Carolina Dept Math Chapel Hill NC 27599 USA Univ Toronto Dept Chem & Phys Sci Mississauga ON L5L 1C6 Canada

Background: Intrinsic fluctuations due to the stochastic nature of biochemical reactions can have large effects on the response of biochemical networks. This is particularly true for pathways that involve transcriptional regulation, where generally there are two copies of each gene and the number of messenger RNA (mRNA) molecules can be small. Therefore, there is a need for computational tools for developing and investigating stochastic models of biochemical networks. Results: We have developed the software package Biochemical Network Stochastic Simulator (BioNetS) for efficiently and accurately simulating stochastic models of biochemical networks. BioNetS has a graphical user interface that allows models to be entered in a straightforward manner, and allows the user to specify the type of random variable (discrete or continuous) for each chemical species in the network. The discrete variables are simulated using an efficient implementation of the Gillespie algorithm. For the continuous random variables, BioNetS constructs and numerically solves the appropriate chemical Langevin equations. The software package has been developed to scale efficiently with network size, thereby allowing large systems to be studied. BioNetS runs as a BioSpice agent and can be downloaded from http://***. BioNetS also can be run as a stand alone package. All the required files are accessible from http://***/BioNetS. Conclusions: We have developed BioNetS to be a reliable tool for studying the stochastic dynamics of large biochemical networks. Important features of BioNetS are its ability to handle hybrid models that consist of both continuous and discrete random variables and its ability to model cell growth and division. We have verified the accuracy and efficiency of the numerical methods by considering several test systems.

关键词： Green Fluorescent Protein Chemical Species Hybrid Model discrete random variable Continuous random variable

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Determination of transformer capacities in an industrial factory with intermittent loads

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IEEE TRANSACTIONS ON POWER DELIVERY 2004年第3期19卷 1253-1258页

作者： Hong, YY Wu, JJ Natl Chung Yuan Univ Dept Elect Engn Chungli 320 Taiwan

The installed transformer capacity can be reduced when the transformer connects intermittent loads with low duty cycles. This paper proposes a new method based on genetic algorithms to determine the transformer capacities for intermittent loads. The costs of transformers are minimized while the voltage fluctuations (drops) satisfy relevant standards. The duration of the voltage drop can be derived from the Markov Process. The intermittent loads are modeled with discrete stochastic distribution;therefore, the generating function is used for aggregating multi-intermittent loads at a bus. Two practical factories with grinders and welders are used to show the applicability of the proposed method.

关键词： discrete random variable genetic algorithms intermittent load Markov process transformer capacity

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A new sampling technique for estimating the mean height

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FOREST ECOLOGY AND MANAGEMENT 2004年第1-3期203卷 311-317页

作者： Ueno, Y Tokyo Univ Agr & Technol Fac Agr Fuchu Tokyo 1838509 Japan

A new sampling technique for easily estimating arithmetic mean height without knowledge of number of trees is proposed. This sampling technique was created by applying the geometrical probability to sampling space that is composed of total number of trees and height, Hmlambda which is greater than the maximum tree height in the forest stand. As a result of a theoretical study, an estimator, Hmlambda, the unbiased estimator of arithmetic mean height was developed, where lambda is a discrete random variable that can take the value 1 if a sample tree is counted;otherwise it is 0. This estimator was tested for spatial patterns that are partly clumped, such as an aggregated distribution, and that are partly uncrowded, such as a random distribution and a regular distribution. Computer simulation was performed by modeling a forest stand and sampling an actual forest stand. This sampling technique was also found to be efficient for aggregated spatial patterns because (P) over cap (mean value of absolute rate of error) and CVgamma (coefficient of variation of an estimator gammaj in die jth computer simulation) obtained by using this sampling technique were stable in four stands with different spatial patterns if 40 points were sampled per stand. This sampling technique may also be effective for stands of partly clumped spatial patterns because it is less time-consuming and have high precision. (C) 2004 Elsevier B.V. All rights reserved.

关键词： discrete random variable sampling space sampling theory simulation spatial pattern

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A model of crop planning under uncertainty in agricultural management

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2003年 81-2卷 555-558页

作者： Itoh, T Ishii, H Nanseki, T Univ Marketing & Distribut Sci Fac Informat Sci Kobe Hyogo 6512188 Japan Osaka Univ Grad Sch Engn Suita Osaka 5650871 Japan Minist Agr Forestry & Fisheries Tsukuba Ibaraki 3058666 Japan

The crop planning problem is often formulated as a linear programming problem. But, in many actual cases, the profit coefficients for agricultural products are not certain values because of the influence of the future weather, so a linear programming model with constant coefficients does not describe the environment of decision making properly. Therefore, we propose a model of crop planning with uncertain (stochastic) values which may support decision making of agricultural farms. In this paper, we treat such uncertain elements as the values with the fuzziness and randomness. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： crop planning linear programming problem fuzzy constraint discrete random variable

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A model of crop planning under uncertainty in agricultural management

A model of crop planning under uncertainty in agricultural m...

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11th International Symposium on Inventories

关键词： crop planning linear programming problem fuzzy constraint discrete random variable

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Generalized variance of Multivariate omega functions and duality

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ANNALS OF OPERATIONS RESEARCH 2002年第1-4期116卷 21-40页

作者： Papayanopoulos, L Rutgers State Univ Sch Business Newark NJ 07102 USA

The covariance of probabilistic variables and the geometry of cones in deterministic optimization traditionally belong in distinct domains of study. This paper aims to show a relationship between the generalized variance of multidimensional joint omega functions and the duality of certain linear programs. Omega distributions are ubiquitous, polymorphic, and multifunctional but have been overlooked, partly due to a lack of closed form. However, the covariance/correlation matrix of joint omega functions can be stated. The geometry that links distributional covariance and generalized variance to the volume of dual cones is an exquisitely simple one.

关键词： weighted binomial combinatorial distribution covariance multivariance volume prior and posterior analysis Bernoulli discrete random variable variance

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Portmanteau test for randomness in Poisson data

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COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION 2000年第4期29卷 1165-1182页

作者： Huber, JC Inst Invent & Innovat Austin TX 78752 USA

While the use of the Portmanteau as a test for randomness in continuous data is well-known, this paper shows it can be applied it to discrete, Poisson data as well. Surprisingly, the Portmanteau test is useful even when the observed counts are small. Also surprising is the finding that small lags are more sensitive for detecting trends and transients than large lags. We show the Portmanteau is superior to the method of runs, the best previous test of randomness for discrete data. These findings allow the Portmanteau test to be used in many quality control applications (such as number of defective parts, machine breakdowns, etc.) as well as human behavior (such as issued patents or even crimes).

关键词： count data discrete random variable homogeneity autocorrelation function serial correlation

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