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  2. Estimation - Wikipedia

    en.wikipedia.org/wiki/Estimation

    Estimation (or estimating) is the process of finding an estimate or approximation, which is a value that is usable for some purpose even if input data may be incomplete, uncertain, or unstable. The value is nonetheless usable because it is derived from the best information available. [ 1 ]

  3. Fermi problem - Wikipedia

    en.wikipedia.org/wiki/Fermi_problem

    A Fermi estimate (or order-of-magnitude estimate, order estimation) is an estimate of an extreme scientific calculation. The estimation technique is named after physicist Enrico Fermi as he was known for his ability to make good approximate calculations with little or no actual data.

  4. Estimation theory - Wikipedia

    en.wikipedia.org/wiki/Estimation_theory

    Estimation theory is a branch of statistics that deals with estimating the values of parameters based on measured empirical data that has a random component. The parameters describe an underlying physical setting in such a way that their value affects the distribution of the measured data.

  5. Estimating equations - Wikipedia

    en.wikipedia.org/wiki/Estimating_equations

    In statistics, the method of estimating equations is a way of specifying how the parameters of a statistical model should be estimated. This can be thought of as a generalisation of many classical methods—the method of moments , least squares , and maximum likelihood —as well as some recent methods like M-estimators .

  6. Estimator - Wikipedia

    en.wikipedia.org/wiki/Estimator

    Bias is a property of the estimator, not of the estimate. Often, people refer to a "biased estimate" or an "unbiased estimate", but they really are talking about an "estimate from a biased estimator", or an "estimate from an unbiased estimator". Also, people often confuse the "error" of a single estimate with the "bias" of an estimator.

  7. Minimax estimator - Wikipedia

    en.wikipedia.org/wiki/Minimax_estimator

    Example 3: Bounded normal mean: When estimating the mean of a normal vector (,), where it is known that ‖ ‖. The Bayes estimator with respect to a prior which is uniformly distributed on the edge of the bounding sphere is known to be minimax whenever M ≤ n {\displaystyle M\leq n\,\!} .

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