isotonic mapping

  • 1Multidimensional scaling — (MDS) is a set of related statistical techniques often used in information visualization for exploring similarities or dissimilarities in data. MDS is a special case of ordination. An MDS algorithm starts with a matrix of item–item similarities,… …

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  • 2List of statistics topics — Please add any Wikipedia articles related to statistics that are not already on this list.The Related changes link in the margin of this page (below search) leads to a list of the most recent changes to the articles listed below. To see the most… …

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  • 3General linear model — Not to be confused with generalized linear model. The general linear model (GLM) is a statistical linear model. It may be written as[1] where Y is a matrix with series of multivariate measurements, X is a matrix that might be a design matrix, B… …

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  • 4Hyperreal number — *R redirects here. For R*, see Rockstar Games. The system of hyperreal numbers represents a rigorous method of treating the infinite and infinitesimal quantities. The hyperreals, or nonstandard reals, *R, are an extension of the real numbers R… …

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  • 5Monte Carlo method — Not to be confused with Monte Carlo algorithm. Computational physics …

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  • 6Meta-analysis — In statistics, a meta analysis combines the results of several studies that address a set of related research hypotheses. In its simplest form, this is normally by identification of a common measure of effect size, for which a weighted average… …

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  • 7Maximum likelihood — In statistics, maximum likelihood estimation (MLE) is a method of estimating the parameters of a statistical model. When applied to a data set and given a statistical model, maximum likelihood estimation provides estimates for the model s… …

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  • 8Ronald Fisher — R. A. Fisher Born 17 February 1890(1890 02 17) East Finchley, London …

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  • 9Coombs test — Diagnostics MeSH D003298 Coombs test (also known as Coombs test, antiglobulin test or AGT) refers to two clinical blood tests used in immunohematology and immunology. The t …

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