### Some articles on *estimators*:

Redescending M-estimator

... In statistics, Redescending M-

... In statistics, Redescending M-

**estimators**are Ψ-type M-**estimators**which have ψ functions that are non-decreasing near the origin, but decreasing toward 0 far from the origin ... Due to these properties of the ψ function, these kinds of**estimators**are very efficient, have a high breakdown point and, unlike other outlier rejection techniques, they do not suffer from a masking effect ...Construction Estimating Software - History - Spreadsheets

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**Estimators**used columnar sheets of paper to organize the take off and the estimate itself into rows of items and columns containing the description, quantity and the pricing components ... With the advent of computers in business,**estimators**began using spreadsheet applications like VisiCalc, Lotus 1-2-3, and Microsoft Excel to duplicate the traditional tabular format ... Many construction cost**estimators**(over 55%) continue to rely primarily upon manual methods, hard copy documents, and/or electronic spreadsheets such as ...Sample Maximum And Minimum - Applications - Estimation

... outliers, the sample extrema cannot reliably be used as

... outliers, the sample extrema cannot reliably be used as

**estimators**unless data is clean – robust alternatives include the first and last deciles ... However, with clean data or in theoretical settings, they can sometimes prove very good**estimators**, particularly for platykurtic distributions, where for small data sets the mid-range is the most ... They are inefficient**estimators**of location for mesokurtic distributions, such as the normal distribution, and leptokurtic distributions, however ...M-estimator

... In statistics, M-

... In statistics, M-

**estimators**are a broad class of**estimators**, which are obtained as the minima of sums of functions of the data ... Least-squares**estimators**and many maximum-likelihood**estimators**are M-**estimators**... The definition of M-**estimators**was motivated by robust statistics, which contributed new types of M-**estimators**...Maximum A Posteriori Estimation - Criticism

... While MAP estimation is a limit of Bayes

... While MAP estimation is a limit of Bayes

**estimators**(under the 0-1 loss function), it is not very representative of Bayesian methods in general ... This is both because these**estimators**are optimal under squared-error and linear-error loss respectively - which are more representative of typical loss ... Finally, unlike ML**estimators**, the MAP estimate is not invariant under reparameterization ...Related Subjects

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