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翻訳と辞書　辞書検索 [ 開発暫定版 ] スポンサード リンク List of stochastic processes topics ： ウィキペディア英語版 List of stochastic processes topics In the mathematics of probability, a stochastic process is a random function. In practical applications, the domain over which the function is defined as a time interval (''time series'') or a region of space (''random field''). Familiar examples of time series include stock market and exchange rate fluctuations, signals such as speech, audio and video; medical data such as a patient's EKG, EEG, blood pressure or temperature; and random movement such as Brownian motion or random walks. Examples of random fields include static images, random topographies (landscapes), or composition variations of an inhomogeneous material. ==Stochastic processes topics== :''This list is currently incomplete.'' See also * Basic affine jump diffusion * Bernoulli process: discrete-time processes with two possible states. * * Bernoulli schemes: discrete-time processes with ''N'' possible states; every stationary process in ''N'' outcomes is a Bernoulli scheme, and vice versa. * Birth-death process * Branching process * Branching random walk * Brownian bridge * Brownian motion * Chinese restaurant process * CIR process * Continuous stochastic process * Cox process *Dirichlet processes * Finite-dimensional distribution * First Passage Time * Galton–Watson process * Gamma process * Gaussian process – a process where all linear combinations of coordinates are normally distributed random variables. * * Gauss–Markov process (cf. below) *Girsanov's theorem *Homogeneous processes: processes where the domain has some symmetry and the finite-dimensional probability distributions also have that symmetry. Special cases include stationary processes, also called time-homogeneous. * Karhunen–Loève theorem * Lévy process * Local time (mathematics) * Loop-erased random walk * Markov processes are those in which the future is conditionally independent of the past given the present. * * Markov chain * * Continuous-time Markov process * * Markov process * * Semi-Markov process * * Gauss–Markov processes: processes that are both Gaussian and Markov *Martingales – processes with constraints on the expectation * Onsager–Machlup function * Ornstein–Uhlenbeck process * Percolation theory *Point processes: random arrangements of points in a space $S$. They can be modelled as stochastic processes where the domain is a sufficiently large family of subsets of ''S'', ordered by inclusion; the range is the set of natural numbers; and, if ''A'' is a subset of ''B'', ''ƒ''(''A'') ≤ ''ƒ''(''B'') with probability 1. * Poisson process * * Compound Poisson process * Population process * Probabilistic cellular automaton * Queueing theory * * Queue * Random field * * Gaussian random field * * Markov random field * Sample-continuous process * Stationary process * Stochastic calculus * * Itō calculus * * Malliavin calculus * * Semimartingale * * Stratonovich integral * Stochastic control * Stochastic differential equation * Stochastic process * Telegraph process * Time series * Wald's martingale * Wiener process 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「List of stochastic processes topics」の詳細全文を読む スポンサード リンク 翻訳と辞書 : 翻訳のためのインターネットリソース Copyright(C) kotoba.ne.jp 1997-2016. All Rights Reserved.