For a time series data set in a linear model, we expect Cov( u1, u2 )...
For a time series data set in a linear model, we expect Cov( u1, u2 ) to be
| A. |
zero. |
|
| B. |
a random variable. |
|
| C. |
nonzero. |
|
| D. |
none of the above |
Homework Answers
In the case of a linear model, the covariance between two error terms is simply zero. Hence the answer is:
{Additional note - If it's non-zero then the linear model suffers from autocorrelation}
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For a time series data set in a linear model, we expect Cov( u1,
u2 )...
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