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Markov Chain Models . . .
, 1993
"... In recent research on extreme value statistics, there has been an extensive development of threshold methods, first in the univariate case but subsequently in the multivariate case as well. In this paper, we develop an alternative methodology for extreme values of univariate time series, by assuming ..."
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, by assuming that the time series is Markovian and using bivariate extreme value theory to suggest appropriate models for the transition distributions. We develop an alternative form of the likelihood representation for threshold methods, and then show how this can be applied to a Markovian time series. A
Numerical Methods in Markov Chain Modelling
 Operations Research
, 1996
"... This paper describes and compares several methods for computing stationary probability distributions of Markov chains. The main linear algebra problem consists of computing an eigenvector of a sparse, nonsymmetric, matrix associated with a known eigenvalue. It can also be cast as a problem of solvi ..."
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Cited by 36 (8 self)
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This paper describes and compares several methods for computing stationary probability distributions of Markov chains. The main linear algebra problem consists of computing an eigenvector of a sparse, nonsymmetric, matrix associated with a known eigenvalue. It can also be cast as a problem
Robustness of the MarkovChain Model for CyberAttack Detection
 IEEE Trans. Reliability
, 2004
"... Abstract—Cyberattack detection is used to identify cyberattacks while they are acting on a computer and network system to compromise the security (e.g., availability, integrity, and confidentiality) of the system. This paper presents a cyberattack detection technique through anomalydetection, a ..."
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Cited by 19 (0 self)
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detection, and discusses the robustness of the modeling technique employed. In this technique, a Markovchain model represents a profile of computerevent transitions in a normal/usual operating condition of a computer and network system (a norm profile). The Markovchain model of the norm profile is generated from
A Markov Chain Model Checker
, 2000
"... . Markov chains are widely used in the context of performance and reliability evaluation of systems of various nature. Model checking of such chains with respect to a given (branching) temporal logic formula has been proposed for both the discrete [17, 6] and the continuous time setting [4, 8]. ..."
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Cited by 57 (22 self)
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. Markov chains are widely used in the context of performance and reliability evaluation of systems of various nature. Model checking of such chains with respect to a given (branching) temporal logic formula has been proposed for both the discrete [17, 6] and the continuous time setting [4, 8
A Markov Chain Model for Statistical Software Testing
 IEEE Transactions on Software Engineering
, 1994
"... Abstruct Statistical testing of software establishes a basis for statistical inference about a software system's expected field quality. This paper describes a method for statistical testing based on a Markov chain model of software usage. The significance of the Markov chain is twofold. First ..."
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Cited by 92 (4 self)
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Abstruct Statistical testing of software establishes a basis for statistical inference about a software system's expected field quality. This paper describes a method for statistical testing based on a Markov chain model of software usage. The significance of the Markov chain is twofold
SpaceOptimized Markov Chain Model for File Prefetching
"... This project investigated the ability of a Markov Chain model to predict file access patterns in OceanStore, a globalscale storage system currently under development. Because a naive implementation of the transition matrix is an inefficient use of memory, we evaluated a simple sparsematrix techniq ..."
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Cited by 1 (0 self)
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This project investigated the ability of a Markov Chain model to predict file access patterns in OceanStore, a globalscale storage system currently under development. Because a naive implementation of the transition matrix is an inefficient use of memory, we evaluated a simple sparse
Introducing Markov Chains Models to Undergraduates
 INTERNATIONAL STATISTICAL INSTITUTE, 53RD SESSION
, 2001
"... ..."
Markov Chain Models of Genetic Algorithms
 In Proceedings of the Genetic and Evolutionary Computation (GECCO) conference
, 1999
"... Nix and Vose [Nix and Vose, 1992] modeled the simple genetic algorithm as a Markov chain, where the Markov chain states are populations. Vose has extended this model to a "Random Heuristic Search" model of genetic (and other) algorithms where each individual of the next generation is selec ..."
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Cited by 9 (1 self)
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Nix and Vose [Nix and Vose, 1992] modeled the simple genetic algorithm as a Markov chain, where the Markov chain states are populations. Vose has extended this model to a "Random Heuristic Search" model of genetic (and other) algorithms where each individual of the next generation
Weighted Markov Chain Model for Musical Composer Identification
"... Abstract. Several approaches based on the ‘Markov chain model ’ have been proposed to tackle the composer identification task. In the paper at hand, we propose to capture phrasing structural information from inter onset and pitch intervals of pairs of consecutive notes in a musical piece, by incorpo ..."
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Cited by 3 (1 self)
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Abstract. Several approaches based on the ‘Markov chain model ’ have been proposed to tackle the composer identification task. In the paper at hand, we propose to capture phrasing structural information from inter onset and pitch intervals of pairs of consecutive notes in a musical piece
MARKOV CHAIN MODEL OF PHYTOPLANKTON DYNAMICS
"... A discretetime stochastic spatial model of plankton dynamics is given. We focus on aggregative behaviour of plankton cells. Our aim is to show the convergence of a microscopic, stochastic model to a macroscopic one, given by an evolution equation. Some numerical simulations are also presented. ..."
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Cited by 1 (0 self)
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A discretetime stochastic spatial model of plankton dynamics is given. We focus on aggregative behaviour of plankton cells. Our aim is to show the convergence of a microscopic, stochastic model to a macroscopic one, given by an evolution equation. Some numerical simulations are also presented.
Results 1  10
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