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Optimal estimation : ウィキペディア英語版 | Optimal estimation In applied statistics, optimal estimation is a regularized matrix inverse method based on Bayes theorem. It is used very commonly in the geosciences, particularly for atmospheric sounding. A matrix inverse problem looks like this: : The essential concept is to transform the matrix, A, into a conditional probability and the variables, and into probability distributions by assuming Gaussian statistics and using empirically-determined covariance matrices. ==Derivation==
Typically, one expects the statistics of most measurements to be Gaussian. So for example for , we can write: : 抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)』 ■ウィキペディアで「Optimal estimation」の詳細全文を読む
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