enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Markov chain - Wikipedia

    en.wikipedia.org/wiki/Markov_chain

    If a Markov chain has a stationary distribution, then it can be converted to a measure-preserving dynamical system: Let the probability space be =, where is the set of all states for the Markov chain. Let the sigma-algebra on the probability space be generated by the cylinder sets.

  3. Stochastic matrix - Wikipedia

    en.wikipedia.org/wiki/Stochastic_matrix

    The stochastic matrix was first developed by Andrey Markov at the beginning of the 20th century, and has found use throughout a wide variety of scientific fields, including probability theory, statistics, mathematical finance and linear algebra, as well as computer science and population genetics. There are several different definitions and ...

  4. Discrete-time Markov chain - Wikipedia

    en.wikipedia.org/wiki/Discrete-time_Markov_chain

    A Markov chain with two states, A and E. In probability, a discrete-time Markov chain (DTMC) is a sequence of random variables, known as a stochastic process, in which the value of the next variable depends only on the value of the current variable, and not any variables in the past.

  5. Markov model - Wikipedia

    en.wikipedia.org/wiki/Markov_model

    The simplest Markov model is the Markov chain.It models the state of a system with a random variable that changes through time. In this context, the Markov property indicates that the distribution for this variable depends only on the distribution of a previous state.

  6. Stochastic process - Wikipedia

    en.wikipedia.org/wiki/Stochastic_process

    In his first paper on Markov chains, published in 1906, Markov showed that under certain conditions the average outcomes of the Markov chain would converge to a fixed vector of values, so proving a weak law of large numbers without the independence assumption, [296] [297] [298] which had been commonly regarded as a requirement for such ...

  7. Continuous-time Markov chain - Wikipedia

    en.wikipedia.org/wiki/Continuous-time_Markov_chain

    A continuous-time Markov chain (CTMC) is a continuous stochastic process in which, for each state, the process will change state according to an exponential random variable and then move to a different state as specified by the probabilities of a stochastic matrix. An equivalent formulation describes the process as changing state according to ...

  8. Absorbing Markov chain - Wikipedia

    en.wikipedia.org/wiki/Absorbing_Markov_chain

    A basic property about an absorbing Markov chain is the expected number of visits to a transient state j starting from a transient state i (before being absorbed). This can be established to be given by the (i, j) entry of so-called fundamental matrix N, obtained by summing Q k for all k (from 0 to ∞).

  9. Multi-compartment model - Wikipedia

    en.wikipedia.org/wiki/Multi-compartment_model

    A multi-compartment model is a type of mathematical model used for describing the way materials or energies are transmitted among the compartments of a system. Sometimes, the physical system that we try to model in equations is too complex, so it is much easier to discretize the problem and reduce the number of parameters.