All Questions
4
questions with no upvoted or accepted answers
2
votes
0
answers
190
views
Understanding Autocovariance under Gaussian Random Process
I'm recently been trying to understand time series better,and would really appreciate if someone can show me this:
I found this online under a lecture slide by J. McJames of Portland Univ., and I ...
1
vote
0
answers
27
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Mean term in simple linear regression
I am trying to derive the expression for the $E(y_i \epsilon_i)$ in simple linear regression. I substitute using $Cov(X,Y) = E(XY) - E(X)E(Y)$, so $E(y_i \epsilon_i) = Cov(y_i , \epsilon_i)- (E(y_i)...
- 111
0
votes
0
answers
76
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Zero conditional expectation implying zero covariance?
Proof: E[X|Y]=0 implies COV[X,Y]=0
I was thinking maybe the law of total covariance or tower rule but couldn't come up with the proof
- 11
0
votes
0
answers
59
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Finding Cov(X,Y) given pdf(X,Y)
Could you please guide me in the right direction for the problem below?
I don't know if I am right, but here is a headstart
Cov(X,Y) = E(XY) - E(X)E(Y)
= $\int_{0}^{\infty}\int_{0}^{\infty} ...
- 101