[R] How can I test if a not independently and not identically distributed time series residuals' are uncorrelated ?

M. M. Palhoto N. Rodrigues mendigo at netcabo.pt
Wed Jan 14 16:52:24 CET 2004

Ok I made Jarque-Bera test to the residuals (merv.reg$residual)

X-squared = 1772.369, df = 2, p-value = < 2.2e-16
And I reject the null hypotesis (H0: merv.reg$residual are normally

So I know that:
1 - merv.reg$residual aren't independently distributed (Box-Ljung test)
2 - merv.reg$residual aren't indentically distributed (Breusch-Pagan test)
3 - merv.reg$residual aren't normally distributed (Jarque-Bera test)

My questions is:
It is possible merv.reg$residual   be uncorrelated ?
cov[residual_t, residual_(t+k)] = 0 ?
Even when residuals  are not independent distributed !
(and we know that they aren't normally distributed and they aren't
indentically distributed )
And how can I tested it ?


> Hint, if a ts is normally distributed then independence and
> are equivalent, hence you can test for normally distributed errors (e.g.
> Jarque-Bera-Test).
> HTH,
> Bernhard
> >

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