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(best linear estimate)

См. также в других словарях:

  • Best linear unbiased prediction — In statistics, best linear unbiased prediction (BLUP) is used in linear mixed models for the prediction of random effects. Best linear unbiased predictions (BLUPs) of random effects are equivalent to best linear unbiased estimates (BLUEs) (see… …   Wikipedia

  • Linear model — In statistics the linear model is given by:Y = X eta + varepsilonwhere Y is an n times;1 column vector of random variables, X is an n times; p matrix of known (i.e. observable and non random) quantities, whose rows correspond to statistical… …   Wikipedia

  • Linear discriminant analysis — (LDA) and the related Fisher s linear discriminant are methods used in statistics, pattern recognition and machine learning to find a linear combination of features which characterize or separate two or more classes of objects or events. The… …   Wikipedia

  • Linear least squares — is an important computational problem, that arises primarily in applications when it is desired to fit a linear mathematical model to measurements obtained from experiments. The goals of linear least squares are to extract predictions from the… …   Wikipedia

  • Linear least squares/Proposed — Linear least squares is an important computational problem, that arises primarily in applications when it is desired to fit a linear mathematical model to observations obtained from experiments. Mathematically, it can be stated as the problem of… …   Wikipedia

  • Linear least squares (mathematics) — This article is about the mathematics that underlie curve fitting using linear least squares. For statistical regression analysis using least squares, see linear regression. For linear regression on a single variable, see simple linear regression …   Wikipedia

  • Least-squares estimation of linear regression coefficients — In parametric statistics, the least squares estimator is often used to estimate the coefficients of a linear regression. The least squares estimator optimizes a certain criterion (namely it minimizes the sum of the square of the residuals). In… …   Wikipedia

  • Least squares — The method of least squares is a standard approach to the approximate solution of overdetermined systems, i.e., sets of equations in which there are more equations than unknowns. Least squares means that the overall solution minimizes the sum of… …   Wikipedia

  • Kriging — is a group of geostatistical techniques to interpolate the value of a random field (e.g., the elevation, z , of the landscape as a function of the geographic location) at an unobserved location from observations of its value at nearby locations.… …   Wikipedia

  • Ordinary least squares — This article is about the statistical properties of unweighted linear regression analysis. For more general regression analysis, see regression analysis. For linear regression on a single variable, see simple linear regression. For the… …   Wikipedia

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

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