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  2. Template:Cite book/testcases/regression tests - Wikipedia

    en.wikipedia.org/wiki/Template:Cite_book/test...

    This is a test cases page for the regression testing of Template:Cite book/testcases to update the examples. If there are many examples of a complicated template, latter ones may break due to limits in MediaWiki, see the HTML comment "NewPP limit report" in the rendered page. You can test how this page looks in the different skins with these links:

  3. Seemingly unrelated regressions - Wikipedia

    en.wikipedia.org/.../Seemingly_unrelated_regressions

    In econometrics, the seemingly unrelated regressions (SUR) [1]: 306 [2]: 279 [3]: 332 or seemingly unrelated regression equations (SURE) [4] [5]: 2 model, proposed by Arnold Zellner in (1962), is a generalization of a linear regression model that consists of several regression equations, each having its own dependent variable and potentially ...

  4. 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

  5. Newey–West estimator - Wikipedia

    en.wikipedia.org/wiki/Newey–West_estimator

    A Newey–West estimator is used in statistics and econometrics to provide an estimate of the covariance matrix of the parameters of a regression-type model where the standard assumptions of regression analysis do not apply. [1] It was devised by Whitney K. Newey and Kenneth D. West in 1987, although there are a number of later variants.

  6. Ordinary least squares - Wikipedia

    en.wikipedia.org/wiki/Ordinary_least_squares

    In statistics, ordinary least squares (OLS) is a type of linear least squares method for choosing the unknown parameters in a linear regression model (with fixed level-one [clarification needed] effects of a linear function of a set of explanatory variables) by the principle of least squares: minimizing the sum of the squares of the differences between the observed dependent variable (values ...

  7. Robust regression - Wikipedia

    en.wikipedia.org/wiki/Robust_regression

    The two regression lines appear to be very similar (and this is not unusual in a data set of this size). However, the advantage of the robust approach comes to light when the estimates of residual scale are considered. For ordinary least squares, the estimate of scale is 0.420, compared to 0.373 for the robust method.

  8. Heteroskedasticity-consistent standard errors - Wikipedia

    en.wikipedia.org/wiki/Heteroskedasticity...

    The ordinary least squares ... White test — a test for whether heteroskedasticity ... see statsmodels.regression.linear_model.RegressionResults for further ...

  9. Durbin–Watson statistic - Wikipedia

    en.wikipedia.org/wiki/Durbin–Watson_statistic

    gretl: Automatically calculated when using OLS regression; Stata: the command estat dwatson, following regress in time series data. [6] Engle's LM test for autoregressive conditional heteroskedasticity (ARCH), a test for time-dependent volatility, the Breusch–Godfrey test, and Durbin's alternative test for serial correlation are also available.