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  2. Linear least squares - Wikipedia

    en.wikipedia.org/wiki/Linear_least_squares

    It is one approach to handling the "errors in variables" problem, and is also sometimes used even when the covariates are assumed to be error-free. Linear Template Fit (LTF) [7] combines a linear regression with (generalized) least squares in order to determine the best estimator. The Linear Template Fit addresses the frequent issue, when the ...

  3. Template:Least squares and regression analysis - Wikipedia

    en.wikipedia.org/wiki/Template:Least_squares_and...

    Main page; Contents; Current events; Random article; About Wikipedia; Contact us; Pages for logged out editors learn more

  4. Linear regression - Wikipedia

    en.wikipedia.org/wiki/Linear_regression

    Like all forms of regression analysis, linear regression focuses on the conditional probability distribution of the response given the values of the predictors, rather than on the joint probability distribution of all of these variables, which is the domain of multivariate analysis. Linear regression is also a type of machine learning algorithm ...

  5. Regression analysis - Wikipedia

    en.wikipedia.org/wiki/Regression_analysis

    The earliest regression form was seen in Isaac Newton's work in 1700 while studying equinoxes, being credited with introducing "an embryonic linear aggression analysis" as "Not only did he perform the averaging of a set of data, 50 years before Tobias Mayer, but summing the residuals to zero he forced the regression line to pass through the ...

  6. Template:Regression bar - Wikipedia

    en.wikipedia.org/wiki/Template:Regression_bar

    Part of a series on: Regression analysis; Models; Linear regression; Simple regression; Polynomial regression; General linear model; Generalized linear model

  7. Coefficient of determination - Wikipedia

    en.wikipedia.org/wiki/Coefficient_of_determination

    Ordinary least squares regression of Okun's law.Since the regression line does not miss any of the points by very much, the R 2 of the regression is relatively high.. In statistics, the coefficient of determination, denoted R 2 or r 2 and pronounced "R squared", is the proportion of the variation in the dependent variable that is predictable from the independent variable(s).