an additive Markov chain is a Markov chain with an additive conditional probability function. Here the process is a discrete-time Markov chain of order...

Gauss–Markov theorem Gauss–Markov process Markov blanket Markov boundary Markov chain Markov chain central limit theorem Additive Markov chain Markov additive...

In applied probability, a Markov additive process (MAP) is a bivariate Markov process where the future states depends only on one of the variables. The...

science Adapted process Adaptive estimator Additive Markov chain Additive model Additive smoothing Additive white Gaussian noise Adjusted Rand index –...

counting measures. The Markov chain is ergodic, so the shift example from above is a special case of the criterion. Markov chains with recurring communicating...

methods, Markov chain Monte Carlo methods, local regression, kernel density estimation, artificial neural networks and generalized additive models. Though...

established a theory of one-to-one correspondence between positive Markov additive functionals and associated measures. This theory and the associated...

Markov additive process Markov blanket / Bay Markov chain mixing time / (L:D) Markov decision process Markov information source Markov kernel Markov logic...

block matrix Q below is a transition rate matrix for a continuous-time Markov chain. Q = [ D 0 D 1 0 0 … 0 D 0 D 1 0 … 0 0 D 0 D 1 … ⋮ ⋮ ⋱ ⋱ ⋱ ] . {\displaystyle...

where the posterior distributions of the models have been obtained by Markov chain Monte Carlo (MCMC) simulation. DIC is an asymptotic approximation as...

distributed random variables Markov chain Moran process Random walk Loop-erased Self-avoiding Biased Maximal entropy Continuous time Additive process Airy process...

}E_{i}\right)=\sum _{i=1}^{\infty }P(E_{i}).} Some authors consider merely finitely additive probability spaces, in which case one just needs an algebra of sets, rather...

bioinformatics Margin Markov chain geostatistics Markov chain Monte Carlo (MCMC) Markov information source Markov logic network Markov model Markov random field...

theory and statistics, diffusion processes are a class of continuous-time Markov process with almost surely continuous sample paths. Diffusion process is...

field. For more information, see § Ordered fields. The property for the additive inverse states that for any real numbers a and b: If a ≤ b, then −a ≥ −b...

of values. He also showed that noise can speed up the convergence of Markov chains to equilibrium. Nonfiction Noise. Viking Press. 2006. ISBN 0-670-03495-9...

Louis. His work is primarily in Bayesian statistics, econometrics, and Markov chain Monte Carlo methods. Chib's research spans a wide range of topics in...

) {\displaystyle O(a+b)} in the general one-dimensional random walk Markov chain. Some of the results mentioned above can be derived from properties of...

sampled empirical measures. In contrast with traditional Monte Carlo and Markov chain Monte Carlo methods these mean-field particle techniques rely on sequential...

the algorithm in Fortran is available from Netlib. Discrepancy theory Markov chain Monte Carlo Quasi-Monte Carlo method Sparse grid Systematic sampling...

Various other numerical methods based on fixed grid approximations, Markov Chain Monte Carlo techniques, conventional linearization, extended Kalman filters...

0)&{\text{ if }}X(t)=0.\end{cases}}} The operator is a continuous time Markov chain and is usually called the environment process, background process or...

be approximated, usually using Laplace approximations or some type of Markov chain Monte Carlo method such as Gibbs sampling. A possible point of confusion...

dynamic systems discretized in the time domain. They are modeled on a Markov chain built on linear operators perturbed by errors that may include Gaussian...

in such a way as to maximize entropy, in analogy with the way that Markov chains assign probabilities to finite-state machine transitions. Systems such...

explaining more details and examples, including a Probability monad for Markov chains. "Functors, Applicatives, And Monads In Pictures (by Aditya Bhargava)...

distributed random variables Markov chain Moran process Random walk Loop-erased Self-avoiding Biased Maximal entropy Continuous time Additive process Airy process...

models (LGMs), for which it can be a fast and accurate alternative for Markov chain Monte Carlo methods to compute posterior marginal distributions. Due...

distributed random variables Markov chain Moran process Random walk Loop-erased Self-avoiding Biased Maximal entropy Continuous time Additive process Airy process...

events in a σ-algebra that satisfies measure properties such as countable additivity. The difference between a probability measure and the more general notion...