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point estimation
In statistics, point estimation involves the use of sample data to calculate a single value (known as a statistic) which is to serve as a "best guess" or "best estimate" of an unknown (fixed or random) population parameter.
More formally, it is the application of a point estimator to the data.
In general, point estimation should be contrasted with interval estimation: such interval estimates are typically either confidence intervals in the case of frequentist inference, or credible intervals in the case of Bayesian inference.
==Point estimators==
*minimum-variance mean-unbiased estimator (MVUE), minimizes the risk (expected loss) of the squared-error loss-function.
*best linear unbiased estimator (BLUE)
*minimum mean squared error (MMSE)
*median-unbiased estimator, minimizes the risk of the absolute-error loss function
*maximum likelihood (ML)
*method of moments, generalized method of moments
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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