On Mon, 28 May 2012, and_mue wrote:
Hi all
I did an estimation of a simple regression model (ror_xxx~ror_spi_xxx) and
assessed the quality of this estimation. After having detected that there
are indications of autocorrelatio and an AR(1) process, I used an arima
model:
absi.arima=arima(ror_absi, order=c(1,0,0), xreg=ror_spi_absi)
Output:
absi.arima
Call:
arima(x = ror_absi, order = c(1, 0, 0), xreg = ror_spi_absi)
Coefficients:
ar1 intercept ror_spi_absi
-0.5377 -1e-04 -0.0060
s.e. 0.0752 3e-04 0.0215
sigma^2 estimated as 1.579e-05: log likelihood = 513.49, aic = -1018.97
This eliminated the arch effect in my model, but I want to check weather
there is still any autocorrelation in my model (with breusch godfrey test,
bgtest). My question is now on how to implement this in the bgtest function.
As there has to be typed in the exact equation of the model or a fitted lm
model, I do not have any idea on what to do now.... Is there a simple
solution for my problem? Same question would be when using the breusch pagan
test.
The bgtest() and bptest() functions from package "lmtest" expect a fitted
"lm" object. To apply them to the residuals of another model you can fit a
simple constant-only model:
m <- lm(residuals(absi.arima) ~ 1)
bgtest(m)
It would probably be more common to consider Box-type tests as conducted
by tsdiag(absi.arima).
hth,
Z
Any suggestions are higly appreciated!
Kind regards,
Andi
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