Kingman (17 December 1992).

141 142 For a sequence of independent and identically distributed random variables X 1, X 2, X 3, displaystyle X_1,X_2,X_3,dots with zero mean, the stochastic process formed from the successive partial sums X 1, X 1 X 2, X 1 X 2 X 3, displaystyle.58 59 One problem is that is it possible to have more than i league 2016 schedule pdf one stochastic process with the same finite-dimensional distributions.Oxford: Oxford University Press Further reading edit External links edit The dictionary definition of stochastic at Wiktionary.See also edit Doob, when citing Khinchin, uses the term 'chance variable which used to be an alternative term for 'random variable'.A b Vere-Jones, David (2006).Wolfgang Paul; Jörg Baschnagel.A b c d e Peter.119 State space edit The mathematical space S displaystyle S of a stochastic process is called its state space.Displaystyle E(M_n1mid M_0,dots,M_n)E(M_nmid M_0,dots,M_n)E(X_n1mid M_0,ldots,M_n)M_nE(X_n1)M_n.Almost surely, a sample path of a Wiener process is continuous everywhere but nowhere differentiable.Stochastic Processes: From Physics to Finance.

Moreover, it is at the heart of the insurance industry.Stochastic Geometry and Its Applications.The law of a stochastic process or a random variable is also called the probability law, probability distribution, or the distribution.Die Doobsche Maximalungleichung liefert eine Abschätzung dafür, welcher Maximalwert eines Martingals bis zu einem gegebenen Zeitpunkt nicht überschritten wird."Half a Century with Probability Theory: Some Personal Recollections".Electronic Journal for History of Probability and Statistics.(Subscription or UK public library membership required.) Bert.To the extent that linguistic knowledge is constituted by experience with language, grammar is argued to be probabilistic and variable rather than fixed and absolute.Finite-dimensional probability distributions edit Main article: Finite-dimensional distribution For a stochastic process X displaystyle X with law displaystyle mu, its finite-dimensional distributions are defined as: t 1, t n P ( X ( t 1 ), X ( t n ) ) 1, displaystyle.