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  2. Breusch–Godfrey test - Wikipedia

    en.wikipedia.org/wiki/Breusch–Godfrey_test

    In Stata, this test is performed by the command estat bgodfrey. [7] [8] In SAS, the GODFREY option of the MODEL statement in PROC AUTOREG provides a version of this test. In Python Statsmodels, the acorr_breusch_godfrey function in the module statsmodels.stats.diagnostic [9]

  3. Free statistical software - Wikipedia

    en.wikipedia.org/wiki/Free_statistical_software

    The free software packages also gave the same regression results as did excel. One of the main differences among the packages was how they handled missing data . With the example data sets used in the review, and for the package versions available in November 2006 when this review was conducted, two packages, MicrOsiris and Epi Info, could read ...

  4. 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.

  5. Heteroskedasticity-consistent standard errors - Wikipedia

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

    RATS: robusterrors option is available in many of the regression and optimization commands (linreg, nlls, etc.). Stata: robust option applicable in many pseudo-likelihood based procedures. [19] Gretl: the option --robust to several estimation commands (such as ols) in the context of a cross-sectional dataset produces robust standard errors. [20]

  6. Correlogram - Wikipedia

    en.wikipedia.org/wiki/Correlogram

    In the analysis of data, a correlogram is a chart of correlation statistics. For example, in time series analysis, a plot of the sample autocorrelations versus (the time lags) is an autocorrelogram. If cross-correlation is plotted, the result is called a cross-correlogram.

  7. Durbin–Watson statistic - Wikipedia

    en.wikipedia.org/wiki/Durbin–Watson_statistic

    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.

  8. Seemingly unrelated regressions - Wikipedia

    en.wikipedia.org/wiki/Seemingly_unrelated...

    In Stata, SUR can be estimated using the sureg and suest commands. [15] [16] [17] In Limdep, SUR can be estimated using the sure command [18] In Python, SUR can be estimated using the command SUR in the “linearmodels” package. [19] In gretl, SUR can be estimated using the system command.

  9. Granger causality - Wikipedia

    en.wikipedia.org/wiki/Granger_causality

    A central aspect of this methodology is the 'tvgc' command in Stata. [23] Empirical applications, such as data involving transaction fees and economic sub-systems on Ethereum, highlight the dynamic nature of economic relationships over time. [25]