4 results for “Markov chains”

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Research ArticleOpen accessPhrase in the titleApplication of Markov Chains to Stock TrendsKevin J. Doubleday, Julius N. EsungeProblem statement: Modeling of the Dow Jones Industrial Average is frequently attempted in order to determine trading strategies with maximum payoff. Changes in the DJIA are important since movements may affect both individuals and corporations profoundly. Previous work showed that modeling a market as a random walk was valid and that a market may be viewed as having the Markov … …Journal of Mathematics and Statistics, Vol. 7, Issue 2 · 18 May 2011 · 8,558 accessesView PDF Cite

Research ArticleOpen accessPhrase in the titleREPRESENTING MARKOV CHAINS WITH TRANSITION DIAGRAMSFarida KachapovaStochastic processes have many useful applications and are taught in several university programmes. Students often encounter difficulties in learning stochastic processes and Markov chains, in particular. In this article we describe a teaching strategy that uses transition diagrams to represent a Markov chain and to re-define properties of its states in simple terms of directed graphs. This strategy utilises the … …Journal of Mathematics and Statistics, Vol. 9, Issue 3 · 17 May 2013 · 7,534 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsReliability of Simple 3-Dimnesional Consecutive k-Out-of-n: F SystemsM. Gharib, E. M. El-Sayed, I.I.H. NashwanProblem statement: In this study, the reliability of some special cases of a 3-dimnesional consecutive k-out-of-n: F system and k-within consecutive (2,2,2) -out-of- (m,2,2): F system were discussed. Approach: The 3 dimensional systems is a generalization of 1 and 2 dimensional, systems. Projections from 3 dimensional systems to 2 or 1 dimension as special cases is very helpful to find … …Journal of Mathematics and Statistics, Vol. 6, Issue 3 · 30 Sep 2010 · 7,443 accessesView PDF Cite

Research ArticleOpen accessIn the abstractMCMC-Fuzzy: A Fuzzy Metric Applied to Bayesian Network Structure LearningBeatriz Wilges, Ademar Crotti Junior, Silvia Modesto NassarBayesian network structure learning is considered a complex task as the number of possible structures grows exponentially with the number of variables. Two main methods are used for Bayesian network structure learning: Conditional independence, a method in which a structure is created consistently with independence tests performed on data; and the heuristic search method that explores the structure space. Hybrid … …Journal of Computer Science, Vol. 14, Issue 8 · 24 Aug 2018 · 8,243 accessesView PDF Cite