...If we know the average value of X ( t ), E ( X ( t ))= m ( t ), and the covariance function E {( X ( t ) -m ( t ))( X ( s ) -m ( s ))}=Γ( t , s ), then the distribution of this Gaussian process, particularly the distribution of the above vector, is uniquely determined. When the time variable t is discrete, it is also called a Gaussian time series, and its detailed properties are known. In particular, when the distribution is invariant over time, that is, in the case of a stationary process, the average value becomes a constant, and Γ( t , s ) becomes a function of only t - s , γ( t - s ). ... *Some of the terminology used to refer to "Gaussian time series" is listed below. Source | Heibonsha World Encyclopedia 2nd Edition | Information |
…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。時間変数tが離散的な場合は,ガウス型時系列とも呼ばれ詳しい性質が知られている。とくにその分布が時間の推移に関して不変な場合,すなわち定常過程の場合は平均値は定数になり,Γ(t,s)はt-sのみの関数γ(t-s)となる。… ※「ガウス型時系列」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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