Score Test for Non-Constant Error Variance
Computes a score test of the hypothesis of constant error variance against the alternative that the error variance changes with the level of the response (fitted values), or with a linear combination of predictors.
ncvTest(model, ...) ## S3 method for class 'lm': ncvTest(model, var.formula, ...) ## S3 method for class 'glm': ncvTest(model, ...) # to report an error
- a weighted or unweighted linear model, produced by
- a one-sided formula for the error variance; if omitted, the error variance depends on the fitted values.
- arguments passed down to methods functions; not currently used.
This test is often called the Breusch-Pagan test; it was independently
suggested with some extension by Cook and Weisberg (1983).
ncvTest.glm is a dummy function to generate an error when a
model is used.
- The function returns a
chisqTestobject, which is usually just printed.
Breusch, T. S. and Pagan, A. R. (1979) A simple test for heteroscedasticity and random coefficient variation. Econometrica 47, 1287--1294. Cook, R. D. and Weisberg, S. (1983) Diagnostics for heteroscedasticity in regression. Biometrika 70, 1--10. Fox, J. (2008) Applied Regression Analysis and Generalized Linear Models, Second Edition. Sage. Fox, J. and Weisberg, S. (2011) An R Companion to Applied Regression, Second Edition, Sage. Weisberg, S. (2014) Applied Linear Regression, Fourth Edition, Wiley.
ncvTest(lm(interlocks ~ assets + sector + nation, data=Ornstein)) ncvTest(lm(interlocks ~ assets + sector + nation, data=Ornstein), ~ assets + sector + nation, data=Ornstein)