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  2. Markov chain - Wikipedia

    en.wikipedia.org/wiki/Markov_chain

    The simplest stochastic models of such networks treat the system as a continuous time Markov chain with the state being the number of molecules of each species and with reactions modeled as possible transitions of the chain. [64] Markov chains and continuous-time Markov processes are useful in chemistry when physical systems closely approximate ...

  3. Transition-rate matrix - Wikipedia

    en.wikipedia.org/wiki/Transition-rate_matrix

    In probability theory, a transition-rate matrix (also known as a Q-matrix, [1] intensity matrix, [2] or infinitesimal generator matrix [3]) is an array of numbers describing the instantaneous rate at which a continuous-time Markov chain transitions between states.

  4. Continuous-time Markov chain - Wikipedia

    en.wikipedia.org/wiki/Continuous-time_Markov_chain

    Transition graph with transition probabilities, exemplary for the states 1, 5, 6 and 8. There is a bidirectional secret passage between states 2 and 8. The image to the right describes a discrete-time Markov chain modeling Pac-Man with state-space {1,2,3,4,5,6,7,8,9}. The player controls Pac-Man through a maze, eating pac-dots.

  5. Discrete phase-type distribution - Wikipedia

    en.wikipedia.org/wiki/Discrete_phase-type...

    The transition matrix is characterized entirely by its upper-left block . Definition. A distribution on {,,,...} is a discrete phase-type distribution if it is the distribution of the first passage time to the absorbing state of a terminating Markov chain with finitely many states.

  6. 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 .

  7. Models of DNA evolution - Wikipedia

    en.wikipedia.org/wiki/Models_of_DNA_evolution

    As a result, it has a unique stationary distribution = {,}, where corresponds to the proportion of time spent in state after the Markov chain has run for an infinite amount of time. In DNA evolution, under the assumption of a common process for each site, the stationary frequencies π A , π G , π C , π T {\displaystyle \pi _{A},\,\pi _{G ...

  8. Stochastic matrix - Wikipedia

    en.wikipedia.org/wiki/Stochastic_matrix

    [1] [2]: 10 It is also called a probability matrix, transition matrix, substitution matrix, or Markov 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 ...

  9. 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 ...