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minimum sum of squared errors

См. также в других словарях:

  • Errors and residuals in statistics — For other senses of the word residual , see Residual. In statistics and optimization, statistical errors and residuals are two closely related and easily confused measures of the deviation of a sample from its theoretical value . The error of a… …   Wikipedia

  • Minimum distance estimation — (MDE) is a statistical method for fitting a mathematical model to data, usually the empirical distribution. Contents 1 Definition 2 Statistics used in estimation 2.1 Chi square criterion …   Wikipedia

  • Minimum description length — The minimum description length (MDL) principle is a formalization of Occam s Razor in which the best hypothesis for a given set of data is the one that leads to the best compression of the data. MDL was introduced by Jorma Rissanen in 1978. It is …   Wikipedia

  • Mean squared error — In statistics, the mean squared error (MSE) of an estimator is one of many ways to quantify the difference between values implied by a kernel density estimator and the true values of the quantity being estimated. MSE is a risk function,… …   Wikipedia

  • Pearson's chi-squared test — (χ2) is the best known of several chi squared tests – statistical procedures whose results are evaluated by reference to the chi squared distribution. Its properties were first investigated by Karl Pearson in 1900.[1] In contexts where it is… …   Wikipedia

  • Chi-squared test — Chi square test is often shorthand for Pearson s chi square test. A chi square test, also referred to as chi squared test or χ2 test, is any statistical hypothesis test in which the sampling distribution of the test statistic is a chi square… …   Wikipedia

  • Linear regression — Example of simple linear regression, which has one independent variable In statistics, linear regression is an approach to modeling the relationship between a scalar variable y and one or more explanatory variables denoted X. The case of one… …   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

  • 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

  • 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

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