transition probabilities

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• probability theory — Math., Statistics. the theory of analyzing and making statements concerning the probability of the occurrence of uncertain events. Cf. probability (def. 4). [1830 40] * * * Branch of mathematics that deals with analysis of random events.… …   Universalium

• Markov chain — A simple two state Markov chain. A Markov chain, named for Andrey Markov, is a mathematical system that undergoes transitions from one state to another, between a finite or countable number of possible states. It is a random process characterized …   Wikipedia

• Moran process — A Moran process, named after Patrick Moran, is a stochastic process used in biology to describe finite populations. It can be used to model variety increasing processes such as mutation as well as variety reducing effects such as genetic drift… …   Wikipedia

• Information bottleneck method — The information bottleneck method is a technique introduced by Tishby et al [1] for finding the best tradeoff between accuracy and complexity (compression) when summarizing (e.g. clustering) a random variable X, given a joint probability… …   Wikipedia

• Quantum superposition — is the fundamental law of quantum mechanics. It defines the allowed state space of a quantum mechanical system.In Probability theory, every possible event has a positive number associated to it, the probability, which gives the chance that it… …   Wikipedia

• Viterbi algorithm — The Viterbi algorithm is a dynamic programming algorithm for finding the most likely sequence of hidden states ndash; called the Viterbi path ndash; that results in a sequence of observed events, especially in the context of Markov information… …   Wikipedia

• Models of DNA evolution — A number of different Markov models of DNA sequence evolution have been proposed. These substitution models differ in terms of the parameters used to describe the rates at which one nucleotide replaces another during evolution. These models are… …   Wikipedia

• Forward-backward algorithm — In computer science, the forward backward algorithm, a dynamic programming algorithm for computing the probability of a particular observation sequence, given the parameters of the model, operates in the context of hidden Markov models. Overview… …   Wikipedia

• Markov decision process — Markov decision processes (MDPs), named after Andrey Markov, provide a mathematical framework for modeling decision making in situations where outcomes are partly random and partly under the control of a decision maker. MDPs are useful for… …   Wikipedia

• Hidden Markov model — Probabilistic parameters of a hidden Markov model (example) x mdash; states y mdash; possible observations a mdash; state transition probabilities b mdash; output probabilitiesA hidden Markov model (HMM) is a statistical model in which the system …   Wikipedia

• Simulated annealing — (SA) is a generic probabilistic meta algorithm for the global optimization problem, namely locating a good approximation to the global optimum of a given function in a large search space. It is often used when the search space is discrete (e.g.,… …   Wikipedia