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In EViews, this test is already done after a regression, at "View" → "Residual Diagnostics" → "Serial Correlation LM Test". In Julia, the BreuschGodfreyTest function is available in the HypothesisTests package. [10] In gretl, this test can be obtained via the modtest command, or under the "Test" → "Autocorrelation" menu entry in the GUI ...
In the book "SPSS For Dummies", the author discusses PSPP under the heading of "Ten Useful Things You Can Find on the Internet". [4] Another review of free to use statistical software also finds that the statistical results from PSPP match statistical results for SAS, for frequencies, means, correlation and regression.
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.
Notably, correlation is dimensionless while covariance is in units obtained by multiplying the units of the two variables. If Y always takes on the same values as X , we have the covariance of a variable with itself (i.e. σ X X {\displaystyle \sigma _{XX}} ), which is called the variance and is more commonly denoted as σ X 2 , {\displaystyle ...
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]
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.
In the panel data fixed effects estimator dummies are created for each of the units in cross-sectional data (e.g. firms or countries) or periods in a pooled time-series. However in such regressions either the constant term has to be removed, or one of the dummies removed making this the base category against which the others are assessed, for ...
MCA is performed by applying the CA algorithm to either an indicator matrix (also called complete disjunctive table – CDT) or a Burt table formed from these variables. [citation needed] An indicator matrix is an individuals × variables matrix, where the rows represent individuals and the columns are dummy variables representing categories of the variables. [1]