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  2. Heckman correction - Wikipedia

    en.wikipedia.org/wiki/Heckman_correction

    The Heckman correction is a two-step M-estimator where the covariance matrix generated by OLS estimation of the second stage is inconsistent. [7] Correct standard errors and other statistics can be generated from an asymptotic approximation or by resampling, such as through a bootstrap. [8]

  3. Standard error - Wikipedia

    en.wikipedia.org/wiki/Standard_error

    This page was last edited on 4 February 2025, at 12:43 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may apply.

  4. Error bar - Wikipedia

    en.wikipedia.org/wiki/Error_bar

    Main page; Contents; Current events; Random article; About Wikipedia; Contact us; Help; Learn to edit; Community portal; Recent changes; Upload file

  5. Bootstrapping (statistics) - Wikipedia

    en.wikipedia.org/wiki/Bootstrapping_(statistics)

    There are at least two ways of performing case resampling. The Monte Carlo algorithm for case resampling is quite simple. First, we resample the data with replacement, and the size of the resample must be equal to the size of the original data set. Then the statistic of interest is computed from the resample from the first step.

  6. Fama–MacBeth regression - Wikipedia

    en.wikipedia.org/wiki/Fama–MacBeth_regression

    "EconTerms - Glossary of Economic Research "Fama–MacBeth Regression" ".Archived from the original on 28 September 2007; Software estimation of standard errors—Page by M. Petersen discussing the estimation of Fama–MacBeth and clustered standard errors in various statistical packages (Stata, SAS, R).

  7. Error function - Wikipedia

    en.wikipedia.org/wiki/Error_function

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  8. Newey–West estimator - Wikipedia

    en.wikipedia.org/wiki/Newey–West_estimator

    In Stata, the command newey produces Newey–West standard errors for coefficients estimated by OLS regression. [13] In MATLAB, the command hac in the Econometrics toolbox produces the Newey–West estimator (among others). [14] In Python, the statsmodels [15] module includes functions for the covariance matrix using Newey–West.

  9. Propagation of uncertainty - Wikipedia

    en.wikipedia.org/wiki/Propagation_of_uncertainty

    Any non-linear differentiable function, (,), of two variables, and , can be expanded as + +. If we take the variance on both sides and use the formula [11] for the variance of a linear combination of variables ⁡ (+) = ⁡ + ⁡ + ⁡ (,), then we obtain | | + | | +, where is the standard deviation of the function , is the standard deviation of , is the standard deviation of and = is the ...