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  2. John Neter - Wikipedia

    en.wikipedia.org/wiki/John_Neter

    John Neter, Student Solutions Manual for Use With Applied Linear Regression Models (3rd) and Applied Linear Statistical Model (4th), (McGraw-Hill College, December 1996) John Neter, Michael H. Kutner, William Wasserman, Christopher J. Nachtscheim, Applied Linear Regression Models , (McGraw-Hill College, January 1996)

  3. Partial regression plot - Wikipedia

    en.wikipedia.org/wiki/Partial_regression_plot

    The least squares linear fit to this plot has an intercept of 0 and a slope , where corresponds to the regression coefficient for X i of a regression of Y on all of the covariates. The residuals from the least squares linear fit to this plot are identical to the residuals from the least squares fit of the original model (Y against all the ...

  4. Linear regression - Wikipedia

    en.wikipedia.org/wiki/Linear_regression

    Download as PDF; Printable version; ... In statistics, linear regression is a model that estimates the linear relationship between a scalar ... Applied Regression ...

  5. Partial leverage - Wikipedia

    en.wikipedia.org/wiki/Partial_leverage

    In regression analysis, partial leverage (PL) is a measure of the contribution of the individual independent variables to the total leverage of each observation. That is, if h i is the i th element of the diagonal of the hat matrix, PL is a measure of how h i changes as a variable is added to the regression model.

  6. Regression analysis - Wikipedia

    en.wikipedia.org/wiki/Regression_analysis

    In linear regression, the model specification is that the dependent variable, is a linear combination of the parameters (but need not be linear in the independent variables). For example, in simple linear regression for modeling n {\displaystyle n} data points there is one independent variable: x i {\displaystyle x_{i}} , and two parameters, β ...

  7. Linear model - Wikipedia

    en.wikipedia.org/wiki/Linear_model

    An example of a linear time series model is an autoregressive moving average model.Here the model for values {} in a time series can be written in the form = + + = + =. where again the quantities are random variables representing innovations which are new random effects that appear at a certain time but also affect values of at later times.

  8. Partial least squares regression - Wikipedia

    en.wikipedia.org/wiki/Partial_least_squares...

    Partial least squares (PLS) regression is a statistical method that bears some relation to principal components regression and is a reduced rank regression; [1] instead of finding hyperplanes of maximum variance between the response and independent variables, it finds a linear regression model by projecting the predicted variables and the observable variables to a new space of maximum ...

  9. Partial residual plot - Wikipedia

    en.wikipedia.org/wiki/Partial_residual_plot

    In applied statistics, a partial residual plot is a graphical technique that attempts to show the relationship between a given independent variable and the response variable given that other independent variables are also in the model.

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