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Observed information : ウィキペディア英語版
Observed information

In statistics, the observed information, or observed Fisher information, is the negative of the second derivative (the Hessian matrix) of the "log-likelihood" (the logarithm of the likelihood function). It is a sample-based version of the Fisher information.
==Definition==
Suppose we observe random variables X_1,\ldots,X_n, independent and identically distributed with density ''f''(''X''; θ), where θ is a (possibly unknown) vector. Then the log-likelihood of the parameters \theta given the data X_1,\ldots,X_n is
:\ell(\theta | X_1,\ldots,X_n) = \sum_^n \log f(X_i| \theta) .
We define the observed information matrix at \theta^ as
:\mathcal(\theta^
*)
= - \left.
\nabla \nabla^
\ell(\theta)
\right|_

::= -
\left.
\left( \begin
\tfrac
& \tfrac
& \cdots
& \tfrac \\
\tfrac
& \tfrac
& \cdots
& \tfrac \\
\vdots &
\vdots &
\ddots &
\vdots \\
\tfrac
& \tfrac
& \cdots
& \tfrac \\
\end \right)
\ell(\theta)
\right|_

In many instances, the observed information is evaluated at the maximum-likelihood estimate.〔Dodge, Y. (2003) ''The Oxford Dictionary of Statistical Terms'', OUP. ISBN 0-19-920613-9〕

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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