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First-order second-moment method : ウィキペディア英語版
First-order second-moment method
In probability theory, the first-order second-moment (FOSM) method, also referenced as mean value first-order second-moment (MVFOSM) method, is a probabilistic method to determine the stochastic moments of a function with random input variables. The name is based on the derivation, which uses a ''first-order'' Taylor series and the first and ''second moments'' of the input variables.〔A. Haldar and S. Mahadevan, Probability, Reliability, and Statistical Methods in Engineering Design. John Wiley & Sons New York/Chichester, UK, 2000.〕
== Approximation ==
Consider the objective function g(x), where the input vector x is a realization of the random vector X with probability density function f_X(x). As X is randomly distributed, also g is randomly distributed.
Following the FOSM method, the mean value of g is approximated by
: \mu_g \approx g(\mu)
The variance of g is approximated by
: \sigma^2_g \approx \sum_^n \sum_^n \frac \frac \operatorname(X_i,X_j)
where n is the length/dimension of x and \frac is the partial derivative of g at the mean vector \mu with respect to the ''i''-th entry of x.

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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