enow.com Web Search

Search results

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

    en.wikipedia.org/wiki/Markov_chain

    Download as PDF; Printable version ... a Markov chain or Markov process is a stochastic process describing a sequence of possible events ... context-free systems and ...

  3. 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.

  4. Markov model - Wikipedia

    en.wikipedia.org/wiki/Markov_model

    A Tolerant Markov model (TMM) is a probabilistic-algorithmic Markov chain model. [6] It assigns the probabilities according to a conditioning context that considers the last symbol, from the sequence to occur, as the most probable instead of the true occurring symbol.

  5. Uniformization (probability theory) - Wikipedia

    en.wikipedia.org/wiki/Uniformization...

    In probability theory, uniformization method, (also known as Jensen's method [1] or the randomization method [2]) is a method to compute transient solutions of finite state continuous-time Markov chains, by approximating the process by a discrete-time Markov chain. [2]

  6. Balance equation - Wikipedia

    en.wikipedia.org/wiki/Balance_equation

    For a continuous time Markov chain (CTMC) with transition rate matrix, if can be found such that for every pair of states and π i q i j = π j q j i {\displaystyle \pi _{i}q_{ij}=\pi _{j}q_{ji}} holds, then by summing over j {\displaystyle j} , the global balance equations are satisfied and π {\displaystyle \pi } is the stationary ...

  7. Birth–death process - Wikipedia

    en.wikipedia.org/wiki/Birth–death_process

    10 Notes. 11 References. ... Download as PDF; Printable version; ... For recurrence and transience in Markov processes see Section 5.3 from Markov chain.

  8. Markov chain Monte Carlo - Wikipedia

    en.wikipedia.org/wiki/Markov_chain_Monte_Carlo

    In statistics, Markov chain Monte Carlo (MCMC) is a class of algorithms used to draw samples from a probability distribution. Given a probability distribution, one can construct a Markov chain whose elements' distribution approximates it – that is, the Markov chain's equilibrium distribution matches the target distribution. The more steps ...

  9. Markovian arrival process - Wikipedia

    en.wikipedia.org/wiki/Markovian_arrival_process

    A Markov arrival process is defined by two matrices, D 0 and D 1 where elements of D 0 represent hidden transitions and elements of D 1 observable transitions. The block matrix Q below is a transition rate matrix for a continuous-time Markov chain.