Message-ID: <248E6FA047A8C746BA491485764190F521FBC4B7@ESESSMB207.ericsson.se>
Date: 2015-05-10T20:25:33Z
From: Giorgio Garziano
Subject: Variance-covariance matrix
In-Reply-To: <CABzE1SiF54_Myu4WCp3EmXKKybTDBWa0gtgUrLRPVCSu9XgE9A@mail.gmail.com>
Hi Tsjerk,
Yes, seriously.
Time series:
X = [x1, x2, x3, ....,xn]
The variance-covariance matrix is V matrix:
V =
? x12 / (N-1)
? x1 x2 / (N-1)
. . .
? x1 xn / (N-1)
? x2 x1 / (N-1)
? x22 / (N-1)
. . .
? x2 xn / (N-1)
. . .
. . .
. . .
. . .
? xn x1 / (N-1)
? xn x2 / (N-1)
. . .
? xn2 / (N-1)
Reference: ?Time series and its applications ? with R examples?, Springer,
$7.8 ?Principal Components? pag. 468, 469
Cheers,
Giorgio
From: Tsjerk Wassenaar [mailto:tsjerkw at gmail.com]
Sent: domenica 10 maggio 2015 22:11
To: Giorgio Garziano
Cc: r-help at r-project.org
Subject: Re: [R] Variance-covariance matrix
Hi Giorgio,
For a univariate time series? Seriously?
data <- rnorm(10,2,1)
as.matrix(var(data))
Cheers,
Tsjerk
On Sun, May 10, 2015 at 9:54 PM, Giorgio Garziano <giorgio.garziano at ericsson.com<mailto:giorgio.garziano at ericsson.com>> wrote:
Hi,
Actually as variance-covariance matrix I mean:
http://stattrek.com/matrix-algebra/covariance-matrix.aspx
that I compute by:
data <- rnorm(10,2,1)
n <- length(data)
data.center <- scale(data, center=TRUE, scale=FALSE)
var.cov.mat <- (1/(n-1)) * data.center %*% t(data.center)
--
Giorgio Garziano
-----Original Message-----
From: David Winsemius [mailto:dwinsemius at comcast.net<mailto:dwinsemius at comcast.net>]
Sent: domenica 10 maggio 2015 21:27
To: Giorgio Garziano
Cc: r-help at r-project.org<mailto:r-help at r-project.org>
Subject: Re: [R] Variance-covariance matrix
On May 10, 2015, at 4:27 AM, Giorgio Garziano wrote:
> Hi,
>
> I am looking for a R package providing with variance-covariance matrix computation of univariate time series.
>
> Please, any suggestions ?
If you mean the auto-correlation function, then the stats package (loaded by default at startup) has facilities:
?acf
# also same help page describes partial auto-correlation function
#Auto- and Cross- Covariance and -Correlation Function Estimation
--
David Winsemius
Alameda, CA, USA
______________________________________________
R-help at r-project.org<mailto:R-help at r-project.org> mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
--
Tsjerk A. Wassenaar, Ph.D.
[[alternative HTML version deleted]]