skedastic (0.1.0)

0 users

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.

Maintainer: Thomas Farrar
Author(s): Thomas Farrar [aut, cre] (<>), University of the Western Cape [cph]

License: MIT + file LICENSE

Uses: broom, car, gmp, het.test, lmtest, lubridate, magrittr, matrixcalc, pracma, Rdpack, Rmpfr, tibble, tseries

Released 3 months ago.



  (0 votes)


  (0 votes)

Log in to vote.


No one has written a review of skedastic yet. Want to be the first? Write one now.

Related packages: BMA, CDNmoney, Ecdat, Hmisc, MNP, Matrix, SparseM, VGAM, aod, bayesm, betareg, boot, bootstrap, car, dynlm, effects, fxregime, gam, gamlss, geepack(20 best matches, based on common tags.)

Search for skedastic on google, google scholar, r-help, r-devel.

Visit skedastic on R Graphical Manual.