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2. Coefficient of multiple correlation - Wikipedia

   en.wikipedia.org/wiki/Coefficient_of_multiple...

   The coefficient of multiple correlation is known as the square root of the coefficient of determination, but under the particular assumptions that an intercept is included and that the best possible linear predictors are used, whereas the coefficient of determination is defined for more general cases, including those of nonlinear prediction and those in which the predicted values have not been ...

3. Frisch–Waugh–Lovell theorem - Wikipedia

   en.wikipedia.org/wiki/Frisch–Waugh–Lovell...

   Yule's formulas for partial regressions were quoted and explicitly attributed to him in order to rectify a misquotation by another author. [10] Although Yule was not explicitly mentioned in the 1933 paper by Frisch and Waugh, they utilized the notation for partial regression coefficients initially introduced by Yule in 1907, which by 1933 was ...

4. Ridge regression - Wikipedia

   en.wikipedia.org/wiki/Ridge_regression

   Ridge regression is a method of estimating the coefficients of multiple-regression models in scenarios where the independent variables are highly correlated. [1] It has been used in many fields including econometrics, chemistry, and engineering. [ 2 ]

5. Multivariate probit model - Wikipedia

   en.wikipedia.org/wiki/Multivariate_probit_model

   In statistics and econometrics, the multivariate probit model is a generalization of the probit model used to estimate several correlated binary outcomes jointly. For example, if it is believed that the decisions of sending at least one child to public school and that of voting in favor of a school budget are correlated (both decisions are binary), then the multivariate probit model would be ...

6. Multivariate statistics - Wikipedia

   en.wikipedia.org/wiki/Multivariate_statistics

   Multivariate regression attempts to determine a formula that can describe how elements in a vector of variables respond simultaneously to changes in others. For linear relations, regression analyses here are based on forms of the general linear model. Some suggest that multivariate regression is distinct from multivariable regression, however ...

7. Linear regression - Wikipedia

   en.wikipedia.org/wiki/Linear_regression

   The simplest case of a single scalar predictor variable x and a single scalar response variable y is known as simple linear regression. The extension to multiple and/or vector-valued predictor variables (denoted with a capital X) is known as multiple linear regression, also known as multivariable linear regression (not to be confused with ...