Dear R help forum members,
I am modeling a gaussian distribution for a computational biology application
and I am working in the statistical package "R". In this regard, my problem is
that I have to construct a covariance matrix with variables (non-numeric) and
the covariance matrix is to be us
I am applying a hidden markov model on joint multivariate gaussian
distribution for 2 vectors. I am using the depmixS4 package in R.
Specifically, I am using the following code:
mod<-depmix(list(response = mom ~ mkt + p0 + p1, mkt~1), data = regvar,
nstates = 2,
family = list(gaussian(), gaussia
On 2011-07-03 04:48, osama hussien wrote:
The backage lmoments computes the L-moments covariances. does anyone
know a backage to compute
the TL-moments covariances
thank
As far as I know the answer is no. But if you study the code of
function varLmoments in package nsRFA and see how closely th
The backage lmoments computes the L-moments covariances. does anyone
know a backage to compute
the TL-moments covariances
thank
--
Osama Abdelaziz Hussien
Department of Statistics
Faculty of Commerce
Alexandria University
Egypt
__
R-help@r-project.org
Let me clarify the output I want to create:
Source X1 (var) X2 (var) X1&X2
(cov)
gen var(X1) var(X2)
cov(x1X2)
block var(X1) var(X2)
cov(x1x2)
error/ res var(
Dear list
I need your help: Execuse me for my limited R knowledge.
#example data set
set.seed (134)
lm=c(1:4)
block = c(rep(lm,6))
gen <- c(rep(1, 4), rep(2, 4), rep(3, 4), rep(4, 4),rep(5, 4),rep(6, 4))
X1 = c( rnorm (4, 10, 4), rnorm (4, 12, 6), rnorm (4, 10, 7),rnorm (4, 5, 2),
rnorm (4, 8,
Hi all,
I generated a covariance matrix and visualized as a 2D contour plot (x,y,
covariance matrix), I would like to extract from the matrix the values ( in
x and y) that auto-correlate which I will plot as an normal (x,y(being the
values that auto-corelate to a certain x and y values in my origi
Unintelligible -- to me anyway. You will have to explain what you mean
more explicitly and with greater clarity -- at least for my feeble
mind-- to get help.
-- Bert Gunter
On Fri, Oct 22, 2010 at 11:01 AM, Marcelo Lima wrote:
> Dear all,
>
> I generated a covariance matrix and I would like to g
Dear all,
I generated a covariance matrix and I would like to generate a 1D plot of
the data that auto-correlate. any suggestions?
Thanks,
Marcelo
--
Marcelo Andrade de Lima
UNIFESP - Universidade Federal de São Paulo
Departamento de Bioquímica
Disciplina de Biologia Molecular
Rua Três de Maio
Dear all,
I'm using R function "glmmPQL" in "MASS" package for generalized linear mixed
model considering the temporal correlations in random effect. There are 1825
observations in my data, in which the random effect is called "Date", and there
are five levels in "Date", each repeats 365 times
R-Help,
I been using nlme to fit a model with 2 random effects. The correlation
matrix I get with the VarCorr command does not seem to have the correct
value for the correlation entry. E.g., below is a VarCorr matrix of random
effects from data that I am working on:
Variance StdDev
Just interchange rows 2 and 3 and then columns 2 and 3 of the original
covariance matrix.
--- On Fri, 8/8/08, Zhang Yanwei - Princeton-MRAm <[EMAIL PROTECTED]> wrote:
> From: Zhang Yanwei - Princeton-MRAm <[EMAIL PROTECTED]>
> Subject: [R] Covariance matrix
> To:
Hi all,
Assume I have a random vector with four variables, i.e. A=(a,b,c,d). I am
able to get the covariance matrix of vector A, but how can I get the covariance
matrix of vector B=(a,c,b,d) by manipulating the corresponding covariance
matrix of A? Thanks.
Sincerely,
Yanwei Zhang
Department
Message-
> From: [EMAIL PROTECTED]
> [mailto:[EMAIL PROTECTED] On Behalf Of A. Beaujean
> Sent: Monday, October 29, 2007 4:25 PM
> To: Peter B. Mandeville
> Cc: r-help
> Subject: Re: [R] covariance matrix of the regression coefficients
>
> If X is your p-1 variable matrix (with
If X is your p-1 variable matrix (with the first column vector being 1s),
i.e., nrow(X)=n and ncol(X)=p
then
MSE<-summary(lm(Y~X[2]+X[3] + ...X[P-1]))$s^2
and your coefficient (co)variance matrix is
MSE*ginv(t(X)%*%X)
Best,
Alex
On 10/29/07, Peter B. Mandeville <[EMAIL PROTECTED]> wrote:
>
>
Dear Peter,
See ?vcov. You could have discovered this via
help.search("covariance").
I hope this helps,
John
On Mon, 29 Oct 2007 11:30:11 -0600
"Peter B. Mandeville" <[EMAIL PROTECTED]> wrote:
> Greetings,
>
>
>
> Cohen, Cohen, West, and Aiken 2003 (Applied Multiple
> Regression-Correlatio
Peter B. Mandeville wrote:
> Greetings,
>
>
>
> Cohen, Cohen, West, and Aiken 2003 (Applied Multiple Regression-Correlation
> Analysis for the Behavioral Sciences, Third Edition) on page 273 state the
> covariance matrix of the regression coefficients is provided by standard
> programs for multip
adhan.html
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On
Behalf Of Peter B. Mandeville
Sent: Monday, October 29, 2007 1:30 PM
To: r-help@r-project.org
Subject: [R] covariance matrix of the regression coefficients
Greetings,
Cohen, Cohen, West, and Aiken 2003 (Applie
See ?vcov .
On Mon, 29 Oct 2007, Peter B. Mandeville wrote:
> Greetings,
>
>
>
> Cohen, Cohen, West, and Aiken 2003 (Applied Multiple Regression-Correlation
> Analysis for the Behavioral Sciences, Third Edition) on page 273 state the
> covariance matrix of the regression coefficients is provided
Greetings,
Cohen, Cohen, West, and Aiken 2003 (Applied Multiple Regression-Correlation
Analysis for the Behavioral Sciences, Third Edition) on page 273 state the
covariance matrix of the regression coefficients is provided by standard
programs for multiple regression, including SAS, SPSS, and S
Greetings,
On page 273, Cohen, Cohen, West, and Aiken (Applied Multiple
Regression/Correlation Analysis for the Behavioral Sciences, Third Edition",
state that the covariance matrix of the regression coefficients is provided by
standard programs for multiple regression, including SAS, SPSS, an
Greetings,
Cohen, Cohen, West, and Aiken 2003 (Applied Multiple Regression-Correlation
Analysis for the Behavioral Sciences, Third Edition) on page 273 state the
covariance matrix of the regression coefficients is provided by standard
programs for multiple regression, including SAS, SPSS, and S
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