…The stochastic process X ( t , w ) (often written as X (t) with w omitted) is a function of the variable t representing time and the parameter w representing chance . When the vector (X( t1 ), X ( t2 ), …, X ( tn ) ) always follows a multidimensional Gaussian distribution for n arbitrarily selected points in time t1 , t2 , …, tn , it is called a Gaussian process or normal process. If the mean value E ( X ( t ) )= m ( t ) of X( t ) and the covariance function E {( X ( t ) -m ( t ))( X ( s )-m( s ))}= Γ ( t , s ) of X( t ) are known, the distribution of this Gaussian process, especially the distribution of the above vector, is uniquely determined. … *Some of the terminology explanations that refer to "Ornstein-Uhlenbeck Brownian motion" are listed below. Source | Heibonsha World Encyclopedia 2nd Edition | Information |
…時間を表す変数tと偶然を表す媒介変数wの関数である確率過程X(t,w)(wは省略して単にX(t)と書くことが多い)は,任意に選んだn個の時点t1,t2,……,tnに対して,ベクトル(X(t1),X(t2),……,X(tn))がいつも多次元ガウス分布に従うとき,ガウス過程あるいは正規過程と呼ばれる。X(t)の平均値E(X(t))=m(t)と共分散関数E{(X(t)-m(t))(X(s)-m(s))}=Γ(t,s)がわかれば,このガウス過程の分布,とくに上記ベクトルの分布は一意的に決まる。… ※「オルンシュタイン=ウーレンベックのブラウン運動」について言及している用語解説の一部を掲載しています。 出典|株式会社平凡社世界大百科事典 第2版について | 情報 |
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