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In statistics and information theory, the expected formation matrix of a likelihood function is the matrix inverse of the Fisher information matrix of , while the observed formation matrix of is the inverse of the observed information matrix of . These matrices appear naturally in the asymptotic expansion of the distribution of many statistics related to the likelihood ratio.

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  • Formation matrix (en)
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  • In statistics and information theory, the expected formation matrix of a likelihood function is the matrix inverse of the Fisher information matrix of , while the observed formation matrix of is the inverse of the observed information matrix of . These matrices appear naturally in the asymptotic expansion of the distribution of many statistics related to the likelihood ratio. (en)
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  • In statistics and information theory, the expected formation matrix of a likelihood function is the matrix inverse of the Fisher information matrix of , while the observed formation matrix of is the inverse of the observed information matrix of . Currently, no notation for dealing with formation matrices is widely used, but in books and articles by Ole E. Barndorff-Nielsen and Peter McCullagh, the symbol is used to denote the element of the i-th line and j-th column of the observed formation matrix. The geometric interpretation of the Fisher information matrix (metric) leads to a notation of following the notation of the (contravariant) metric tensor in differential geometry. The Fisher information metric is denoted by so that using Einstein notation we have . These matrices appear naturally in the asymptotic expansion of the distribution of many statistics related to the likelihood ratio. (en)
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