Displaying 3 results from an estimated 3 matches for "residual_".
Did you mean:
residuals
2004 Jan 13
3
How can I test if a not independently and not identically distributed time series residuals' are uncorrelated ?
...use 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$residuals are uncorrelated ?
Thanks a lot.
[[alternative HTML version deleted]]
2004 Jan 14
3
How can I test if time series residuals' are uncorrelated ?
...merv.reg$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$residual be uncorrelated ?
cov[residual_t, residual_(t+k)] = 0 ?
Even when residuals are not independent distributed !
(and we know that they aren't normally distributed and they aren't
indentically distributed )
And how can I tested it ?
Thanks.
> Hint, if a ts is normally distributed then independence and
uncorrelatedness...
2004 Jan 14
0
How can I test if a not independently and not identicallydistributed time series residuals' are uncorrelated ?
...use the residuals are not independently distributed, we know that the
squares of residuals are correlated:
cov[(residuals_t)^2, (residuals_(t-k))^2] <> 0 (not zero for k <> 0)
But, the residuals could be uncorrelated, (even when they
are not independent distributed):
cov[residuals_t, residual_(t-k)]=0 !
How can I test that merv.reg$residuals are uncorrelated ?
Thanks a lot.
[[alternative HTML version deleted]]