Heteroskedasticity Diagnostics for Linear Regression Models

Implements numerous methods for detecting heteroskedasticity (sometimes called heteroscedasticity) in the classical linear regression model. These include the parametric and nonparametric tests of Goldfeld and Quandt (1965) , the test of Glejser (1969) as formulated by Mittelhammer, Judge and Miller (2000, ISBN: 0-521-62394-4), the BAMSET Test of Ramsey (1969) , which uses the BLUS residuals derived by Theil (1965) , the test of Harvey (1976) , the test of Breusch and Pagan (1979) with and without the modification proposed by Koenker (1981) , the test of White (1980) , the test and graphical Cook and Weisberg (1983) , and the test of Li and Yao (2019) . Homoskedasticity refers to the assumption of constant variance that is imposed on the model errors (disturbances); heteroskedasticity is the violation of this assumption.


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("skedastic")

0.1.0 by Thomas Farrar, 3 months ago


http://github.com/tjfarrar/skedastic


Report a bug at http://github.com/tjfarrar/skedastic/issues


Browse source code at https://github.com/cran/skedastic


Authors: Thomas Farrar [aut, cre] , University of the Western Cape [cph]


Documentation:   PDF Manual  


Task views: Econometrics


MIT + file LICENSE license


Imports stats, utils, Rdpack, tibble, broom, magrittr, pracma, gmp, Rmpfr, matrixcalc, lubridate, lmtest, car, het.test, tseries


See at CRAN