Take the 2-minute tour ×
Cross Validated is a question and answer site for people interested in statistics, machine learning, data analysis, data mining, and data visualization. It's 100% free, no registration required.

The definition for the $k$-th lag auto correlation is $Cov(y_t,y_{t-k})/Var(y_t)$.
My question is why should not it be $Cov(y_t,y_{t-k})/[Var(y_t)\cdot Var(y_{t-k})]^{0.5}$.
In another words, what is it different from the correlation coefficient between $y_t$ and $y_{t-k}$?

share|improve this question
    
I guessed the question, since you probably hit post too soon. See if it is ok. –  mpiktas Jun 20 '11 at 6:48
add comment

1 Answer

Auto-correlation is defined for stationary processes. The stationary process has constant mean and constant variance, hence $Var(y_t)=Var(y_{t-k})$ for all $t$ and $k$. With this in mind the definitions coincide.

share|improve this answer
add comment

Your Answer

 
discard

By posting your answer, you agree to the privacy policy and terms of service.

Not the answer you're looking for? Browse other questions tagged or ask your own question.