14 Facts About Markov chain

Markov chain or Markov process is a stochastic model describing a sequence of possible events in which the probability of each event depends only on the state attained in the previous event.

Markov chain process is a stochastic process that satisfies the Markov chain property .

Markov chain is a type of Markov process that has either a discrete state space or a discrete index set, but the precise definition of a Markov chain varies.

Notice that the general state space continuous-time Markov chain is general to such a degree that it has no designated term.

Markov chain studied Markov chain processes in the early 20th century, publishing his first paper on the topic in 1906.

Markov chain was interested in studying an extension of independent random sequences, motivated by a disagreement with Pavel Nekrasov who claimed independence was necessary for the weak law of large numbers to hold.

Markov chain introduced and studied a particular set of Markov processes known as diffusion processes, where he derived a set of differential equations describing the processes.

Discrete-time Markov chain is a sequence of random variables X1, X2, X3,.

An algorithm based on a Markov chain was used to focus the fragment-based growth of chemicals in silico towards a desired class of compounds such as drugs or natural products.

Markov chain models have been used to analyze web navigation behavior of users.

Markov chain methods have become very important for generating sequences of random numbers to accurately reflect very complicated desired probability distributions, via a process called Markov chain Monte Carlo .

Second-order Markov chain can be introduced by considering the current state and the previous state, as indicated in the second table.

Markov chain models have been used in advanced baseball analysis since 1960, although their use is still rare.

Markov chain discusses various kinds of strategies and play conditions: how Markov chain models have been used to analyze statistics for game situations such as bunting and base stealing and differences when playing on grass vs AstroTurf.