[R] Variance-covariance matrix

Giorgio Garziano giorgio.garziano at ericsson.com
Sun May 10 22:25:33 CEST 2015


Hi Tsjerk,

Yes, seriously.

Time series:

X = [x1, x2, x3, ....,xn]

The variance-covariance matrix is V matrix:

            V    =


Σ x12 / (N-1)

Σ x1 x2 / (N-1)

. . .

Σ x1 xn / (N-1)

Σ x2 x1 / (N-1)

Σ x22 / (N-1)

. . .

Σ x2 xn / (N-1)

. . .

. . .

. . .

. . .

Σ xn x1 / (N-1)

Σ xn x2 / (N-1)

. . .

Σ 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

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--
Tsjerk A. Wassenaar, Ph.D.

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