On Fri, 16 Oct 2009, Gautier RENAULT wrote:
Hi r-programmers,
I performe Breusch-Pagan tests (bptest in package lmtest) to check the
homoscedasticity of the residuals from a linear model and I carry out carry
out White's test via
bptest (formula, ~ x * z + I(x^2) + I(z^2)) include all regressors and the
squares/cross-products in the auxiliary regression.
But what can I do if I want find coefficient and p-values of variables x, z,
x*z, I(x^2), I(z^2) ? **I wish find out which is responsible of
heteroscedasticity...
To take a reproducible example (cigarette consumption from Baltagi's
book):
## packages and data
library("AER")
data("CigarettesB")
## regression
cig_lm2 <- lm(packs ~ price + income, data = CigarettesB)
## White test
bptest(cig_lm2, ~ income * price + I(income^2) + I(price^2),
data = CigarettesB)
The auxiliary regression that is used in this test cannot be extracted
from bptest() but you can easily run it yourself by hand:
## auxiliary regression
aux <- residuals(cig_lm2)^2 - mean(residuals(cig_lm2)^2)
aux_lm <- lm(aux ~ income * price + I(income^2) + I(price^2),
data = CigarettesB)
The test statistic is then the n * R-squared:
## test statistic
nrow(CigarettesB) * summary(aux_lm)$r.squared
And then you can also look at the details of the auxiliary model:
summary(aux_lm)
However, this does not have to be very conclusive as in this particular
example...
hth,
Z
Can anyone help?
thanking you in advance,
Gautier RENAULT
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