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residuals
2004 Jan 13
3
How can I test if a not independently and not identically distributed time series residuals' are uncorrelated ?
...25,type="Ljung")
X-squared = 54.339, df = 25, p-value = 0.0006004
So, there is evidence to not reject the null hypothesis,
than the residuals are independently distributed.
Because the residuals are not independently distributed, we know that the
squares of residuals are correlated:
cov[(residuals_t)^2, (residuals_(t-k))^2] <> 0 (not zero for k <> 0)
But, the residuals could be uncorrelated, (even when they
are not independent distributed):
cov[residuals_t, residual_(t-k)]=0 !
How can I test that merv.reg$residuals are uncorrelated ?
Thanks a lot.
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2004 Jan 14
0
How can I test if a not independently and not identicallydistributed time series residuals' are uncorrelated ?
...X-squared = 54.339, df = 25, p-value = 0.0006004
So, there is evidence to REGECT (mistake in laste e-mail)
the null hypothesis,
than the residuals are NOT independently distributed.
Because the residuals are not independently distributed, we know that the
squares of residuals are correlated:
cov[(residuals_t)^2, (residuals_(t-k))^2] <> 0 (not zero for k <> 0)
But, the residuals could be uncorrelated, (even when they
are not independent distributed):
cov[residuals_t, residual_(t-k)]=0 !
How can I test that merv.reg$residuals are uncorrelated ?
Thanks a lot.
[[alternative HTML version...