half Of livia
> Sent: Friday, July 13, 2007 6:00 AM
> To: r-help@stat.math.ethz.ch
> Subject: [R] correlation matrix difference
>
>
> Hi, I have got four correlation matrix. They are the same set
> of variables under different conditions. Is there a way to
> test whether the
[mailto:[EMAIL PROTECTED]
Sent: July 13, 2007 10:51 AM
To: Caskenette, Amanda
Cc: r-help@stat.math.ethz.ch
Subject: Re: [R] Correlation matrix
Caskenette, Amanda wrote:
> I have a model with 5 parameters that I am optimising where the (best)
> value of the objective function is negative. I
Caskenette, Amanda wrote:
> I have a model with 5 parameters that I am optimising where the (best)
> value of the objective function is negative. I would like to use the
> Hessian matrix (from genoud and/or optim functions) to construct the
> covariance and correlation matrices.
>
> This is the
I have a model with 5 parameters that I am optimising where the (best)
value of the objective function is negative. I would like to use the
Hessian matrix (from genoud and/or optim functions) to construct the
covariance and correlation matrices.
This is the code that I am using:
est <- out
Hi, I have got four correlation matrix. They are the same set of variables
under different conditions. Is there a way to test whether the correlation
matrix are significently different among each other? Could
anyone give me some advice?
--
View this message in context:
http://www.nabble.com/cor
Arun Kumar Saha wrote:
> Dear R users,
>
> Suppose I have a 4*5 data frame like this:
>
> Date x1 x2 x3 x4
> 1/1/2004100 22 12 34
> 2/1/200433-22 33 12
> 3/1/20041212 -115
> 4/1/20041 223 22 1
Dear R users,
Suppose I have a 4*5 data frame like this:
Date x1 x2 x3 x4
1/1/2004100 22 12 34
2/1/200433-22 33 12
3/1/20041212 -115
4/1/20041 223 22 1
Now I want to get a correlation matrix fo
Serguei Kaniovski wifo.ac.at> writes:
>
> I've a vector of pairwise correlations in the order low-index element
> precedes the high-index element, say:
>
> corr(1,2)=0.1, corr(1,3)=0.2, corr(2,3)=0.3, corr(3,4)=0.4
>
> How can I construct the corresponding correlation matrix?
Not absolutel
I've a vector of pairwise correlations in the order low-index element
precedes the high-index element, say:
corr(1,2)=0.1, corr(1,3)=0.2, corr(2,3)=0.3, corr(3,4)=0.4
How can I construct the corresponding correlation matrix?
I tried using the "combn"-function in "combinat" package:
library(com
Excellent! This is the most flexible and intuitive option. Thanks!
Omer
Cell: (914) 671-7447
-Original Message-
From: Liaw, Andy [mailto:[EMAIL PROTECTED]
Sent: Friday, June 17, 2005 8:40 AM
To: '[EMAIL PROTECTED]'; r-help@stat.math.ethz.ch
Subject: RE: [R] CORRELAT
Something like:
> dat <- data.frame(x=runif(10), y=runif(10), z=runif(10))
> m <- cor(dat)
> m
x y z
x 1.000 0.1183305 0.1096394
y 0.1183305 1.000 -0.2819285
z 0.1096394 -0.2819285 1.000
> mat2col <- function(m) {
+ m2 <- matrix(m, ncol=1)
+ rown
Maybe like:
> dat
X Y Z
X 1.0 0.9 0.5
Y 0.9 1.0 0.1
Z 0.5 0.1 1.0
> datrow <- stack(as.data.frame(dat))
> datrow$X=rownames(dat)
> datrow
values ind X
11.0 X X
20.9 X Y
30.5 X Z
40.9 Y X
51.0 Y Y
60.1 Y Z
70.5 Z X
80.1 Z Y
91.0
Omer Bakkalbasi wrote:
> How do I convert the output of cor(x) to a columnar format?
> Ex. from format below
> XYZ
> X 1.0 0.9 0.5
> Y 0.9 1.0 0.1
> Z 0.5 0.1 1.0
>
> to format below
>
> X X 1.0
> X Y 0.9
> X Z 0.5
> Y X 0.9
> Y Y 1.0
> Y Z 0.1
> Z X 0.5
> Z Y 0.1
> Z Z 1.0
How do I convert the output of cor(x) to a columnar format?
Ex. from format below
XYZ
X 1.0 0.9 0.5
Y 0.9 1.0 0.1
Z 0.5 0.1 1.0
to format below
X X 1.0
X Y 0.9
X Z 0.5
Y X 0.9
Y Y 1.0
Y Z 0.1
Z X 0.5
Z Y 0.1
Z Z 1.0
Thanks!
Omer
___
Liliana Forzani wrote:
Hi, I have data normal with mean 0, I was wondering how to get (using R)
the best r such that the correlation matrix of my data has the form
{r^(i-j)} where (i,j) indicate row and columm respectivly. Thanks. Liliana
Thats the correlation matrix for an autoregressive(1) pro
390867/dimitris.htm
- Original Message -
From: "Liliana Forzani" <[EMAIL PROTECTED]>
Cc: "R-News" <[EMAIL PROTECTED]>
Sent: Wednesday, December 08, 2004 3:32 PM
Subject: [R] correlation matrix o
Hi, I have data normal with mean 0, I was wondering how to get
(u
Hi, I have data normal with mean 0, I was wondering how to get (using R)
the best r such that the correlation matrix of my data has the form
{r^(i-j)} where (i,j) indicate row and columm respectivly. Thanks. Liliana
__
[EMAIL PROTECTED] mailing list
h
Hi Sundar,
many thanks for your suggestion: it's just I wished!
Best
Vito
--- Sundar Dorai-Raj <[EMAIL PROTECTED]> ha
scritto:
>
>
> Vito Ricci wrote:
>
> > Hi,
> >
> > I'm dealing with a datamining analysis: I've a lot
> of
> > categories of product sold per week (n. week =26,
> n.
> > ca
Vito Ricci wrote:
Hi,
I'm dealing with a datamining analysis: I've a lot of
categories of product sold per week (n. week =26, n.
categories about 50.
my dataframe is like this:
Settimana ALIMENTI..ALTRI. ALIMENTI.APROTEICI
1 13 19
2 2
Hi,
I'm dealing with a datamining analysis: I've a lot of
categories of product sold per week (n. week =26, n.
categories about 50.
my dataframe is like this:
Settimana ALIMENTI..ALTRI. ALIMENTI.APROTEICI
1 13 19
2 22
On Fri, 17 Oct 2003 16:36:47 +0200
Luca De Benedictis <[EMAIL PROTECTED]> wrote:
> Dear all,
> I am trying to compute a matrix of Pearson's `r' or Spearman's `rho'
> rank correlation coefficients using rcorr (Hmisc) the following way:
>
> > mx<-rcorr(x, type="spearman")[1]
Instead of [1] use
Dear all,
I am trying to compute a matrix of Pearson's `r' or Spearman's `rho'
rank correlation coefficients using rcorr (Hmisc) the following way:
> mx<-rcorr(x, type="spearman")[1]
but then ...
> is.matrix(mx)
[1] FALSE
Even if I use as.matrix the result is not better.
What can I do?
Thank
Dear all,
I have T Y variables, Y1,...,YT, which are T repeated observations on a
variable over the T waves of a survey.
I'd like to estimate a correlation matrix cor(Y1,...,YT) assuming specific
structures, as for example exchangeable, stationary, autoregressive and
nonstationary.
Is there a
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