ll open a
> separate thread
> in the case.
>
> Thanks.
>
> ---
>
> Giorgio
>
> Genoa, Italy
>
> From: Tsjerk Wassenaar [mailto:tsje...@gmail.com]
> Sent: domenica 10 maggio 2015 22:31
> To: Giorgio Garziano
> Cc: r-help@r-project.org
> Subject: Re: [R] Va
: Re: [R] Variance-covariance matrix
Hi Giorgio,
This is for a multivariate time series. x1 is variable 1 of the observation
vector x, x2, variable 2, etc. If you need x(i) and x(i+1), etc, then you're
looking for the autocovariance/autocorrelation matrix, which is a quite
different thing
nce: “Time series and its applications – with R examples”,
> Springer,
>
> $7.8 “Principal Components” pag. 468, 469
>
>
>
> Cheers,
>
>
>
> Giorgio
>
>
>
>
>
> *From:* Tsjerk Wassenaar [mailto:tsje...@gmail.com]
> *Sent:* domenica 10 mag
-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
mailto:giorgio.garzi...@ericsson.com>> wrote:
Hi,
Actually as
ata.center)
>
> --
> Giorgio Garziano
>
>
> -Original Message-
> From: David Winsemius [mailto:dwinsem...@comcast.net]
> Sent: domenica 10 maggio 2015 21:27
> To: Giorgio Garziano
> Cc: r-help@r-project.org
> Subject: Re: [R] Variance-covariance matrix
>
&g
lt;- (1/(n-1)) * data.center %*% t(data.center)
--
Giorgio Garziano
-Original Message-
From: David Winsemius [mailto:dwinsem...@comcast.net]
Sent: domenica 10 maggio 2015 21:27
To: Giorgio Garziano
Cc: r-help@r-project.org
Subject: Re: [R] Variance-covariance matrix
On May 10, 2015, at 4:27
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
Fantastic! it's solved! Thank you very much Bill!
Barbara
--- On Wed, 7/28/10, bill.venab...@csiro.au wrote:
> From: bill.venab...@csiro.au
> Subject: RE: [R] Variance-covariance matrix from GLM
> To: bojuanz...@yahoo.com, r-help@r-project.org
> Date: Wednesday, July
?vcov ### now in the stats package
You would use
V <- vcov(my.glm)
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of Bojuan Zhao
Sent: Thursday, 29 July 2010 9:52 AM
To: r-help@r-project.org
Subject: [R] Variance-covariance matr
Laura Bonnett wrote:
> Here is the exact code I have written which does the standard vs nt1
> and standard vs nt2 and also gives me the hazard ratio for nt1 vs nt2.
>
> with <- read.table("allwiths.txt",
> header=TRUE)
> fix(arm)
> function (data)
> {
> dummy <- rep(0,2437)
> for(i
Here is the exact code I have written which does the standard vs nt1 and
standard vs nt2 and also gives me the hazard ratio for nt1 vs nt2.
with <- read.table("allwiths.txt",header=TRUE)
fix(arm)
function (data)
{
dummy <- rep(0,2437)
for(i in 1:2437){
if(data$Arm[i]=="CBZ")
Laura Bonnett wrote:
> Hi all,
>
> Sorry to ask again but I'm still not sure how to get the full
> variance-covariance matrix. Peter suggested a three-level treatment
> factor. However, I thought that the censoring variable could only take
> values 0 or 1 so how do you programme such a factor.
>
Hi all,
Sorry to ask again but I'm still not sure how to get the full
variance-covariance matrix. Peter suggested a three-level treatment
factor. However, I thought that the censoring variable could only take
values 0 or 1 so how do you programme such a factor.
Alternatively, is there another w
The standard treatment is the same in both comparison.
How do you do a three-level treatment factor?
I thought you had to have a censoring indicator which took values 0 or 1 not
1, 2 or 3?
Thanks,
Laura
On Tue, Aug 26, 2008 at 11:05 AM, Peter Dalgaard
<[EMAIL PROTECTED]>wrote:
> Laura Bonnett
Laura Bonnett wrote:
> Dear R help forum,
>
> I am using the function 'coxph' to obtain hazard ratios for the comparison
> of a standard treatment to new treatments. This is easily obtained by
> fitting the relevant model and then calling exp(coef(fit1)) say.
>
> I now want to obtain the hazard ra
mea culpa: I've not written an extractor for this, so you have to do
f <- nlrq(whatever)
g <- summary(f)
g$cov
Note that this is computed by resampling so it varies somewhat
depending on the seed.
url:www.econ.uiuc.edu/~rogerRoger Koenker
email[EM
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