Talk:Autocovariance

Wiki Education Foundation-supported course assignment

File:Sciences humaines.svg This article is or was the subject of a Wiki Education Foundation-supported course assignment. Further details are available on the course page. Student editor(s): Kezhoulumelody. Peer reviewers: Kezhoulumelody.

Above undated message substituted from Template:Dashboard.wikiedu.org assignment by PrimeBOT (talk) 15:03, 16 January 2022 (UTC)

autocorrelation

The previous suggestion that the autocovariance was the autocorrelation of a process with zero mean was just plain wrong. I thought this page could use extensive revision to bring it into line with the definition of covariance.

Richard Clegg

explain s

In

$C_{XX}(t,s)=cov(X_t,X_s)=E[(X_t-{\mu }_t)(X_s-{\mu }_s)]=E[X_t{X}_s]-{\mu }_t{\mu }_s.$

must explain what is s. --Krauss (talk) 07:42, 24 October 2014 (UTC)

External links modified

Hello fellow Wikipedians,

I have just modified one external link on Autocovariance. Please take a moment to review my edit. If you have any questions, or need the bot to ignore the links, or the page altogether, please visit this simple FaQ for additional information. I made the following changes:

• Added archive https://web.archive.org/web/20060428122150/http://w3eos.whoi.edu:80/12.747/notes/lect06/l06s02.html to http://w3eos.whoi.edu/12.747/notes/lect06/l06s02.html

When you have finished reviewing my changes, please set the checked parameter below to true or failed to let others know (documentation at Template:Tlx).

Cheers.—InternetArchiveBot (Report bug) 05:28, 22 October 2016 (UTC)

explain weakly stationary process

In If X(t) is a weakly stationary process, then the following are true:

${\mu }_t={\mu }_s=\mu$ for all t, s

and

$C_{XX}(t,s)=C_{XX}(s-t)=C_{XX}(\tau )$

where $\tau =|s-t|$ is the lag time, or the amount of time by which the signal has been shifted.

Please explain more about it.

${\mu }_t,{\mu }_s,C_{XX}(t,s)$ and :$C_{XX}(s-t)$can not be found in link provided

--Kezhoulumelody (talk) 13:44, 26 April 2017 (UTC)

explain linearly filtered process

In The autocovariance of a linearly filtered process $Y_t$

$Y_t=\sum _{k=-\mathrm{\infty }}^{\mathrm{\infty }}{a}_k{X}_{t+k}$

is

$C_{YY}(\tau )=\sum _{k,l=-\mathrm{\infty }}^{\mathrm{\infty }}{a}_k{a}_l{C}_{XX}(\tau +k-l).$

Explain linearly filtered process and what properties the autocovariance will have if it is not a linearly filtered process.

--Kezhoulumelody (talk) 13:51, 26 April 2017 (UTC)