Dear Sebastian,
I was able to replicate the R^2 value of 0.993019 using the function provided
as the second answer (by Julien Massardier) to the following question -
https://stats.stackexchange.com/questions/83826/is-a-weighted-r2-in-robust-linear-model-meaningful-for-goodness-of-fit-analys
Tha
Hi,
recently I posted a question about how R computes the value for the
"r.squared" statistic internally for weighted least squares linear
models on crossvalidated.com (see:
https://stats.stackexchange.com/questions/439590/how-does-r-compute-r-squared-for-weighted-least-squares)
including a m
In this calculation:
(dg0%*%t(dx0))
is
[,1] [,2]
[1,]0 -0.75
[2,]0 0.50
So: exp2 = NaN
It is extremely easy to find out the issue if you go back line by line,
this is a basic procedure of debugging. Please do it yourself next time.
On Mon, Jan 13, 2014 at 3:09 PM, IZHAK shabso
-help-boun...@r-project.org [mailto:r-help-bounces@r-
> project.org] On Behalf Of IZHAK shabsogh
> Sent: Monday, January 13, 2014 8:10 AM
> To: r-help@r-project.org
> Subject: [R] computation
>
> kindly help me fine what is the mistake with following: my aim is to
> compute those s
kindly help me fine what is the mistake with following:
my aim is to compute those steps and obtain a vector with values (3,5)
but i am geting (NAN,NAN)
Q<-matrix(c(5,-3,-3,2),2,2)
b<-rbind(0,1)
H0<-diag(2)
x0<-rbind(0,0)
d0<-b
g0<--b
a0<--(t(g0)%*%d0)/(t(d0)%*%Q%*%d0)
x1<-x0+a0[,1]*d0
dx0<-x1-x
On Sunday, November 3, 2013 3:17 PM, IZHAK shabsogh wrote:
Hi,
another problem after getting the above hessian matrix i am suppose to use it
and fine the sum of the product
of the hessian and the residuals, for the hessian is generated from the above
while the residual is also obtain from
On 1 November 2013 11:06, IZHAK shabsogh wrote:
> below is a code to compute hessian matrix , which i need to generate 29
> number of different matrices for example first
You may consider using Numerical Derivatives package for that instead, see:
http://cran.r-project.org/web/packages/numDeriv/v
below is a code to compute hessian matrix , which i need to generate 29 number
of different matrices for example first element in x1 and x2 is use to generate
let say matrix (M1) and second element in x1 and x2 give matrix (M2) upto
matrix (M29) corresponding to the total number of observations
?Rprof
or
?system.time
TGS wrote:
Is there a way to find out what the computation duration time was to complete
executing a code chunk?
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guid
Is there a way to find out what the computation duration time was to complete
executing a code chunk?
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guid
ecs for the dominant
eigenvalue and corresponding eigenvector.
How very large is your matrix?
Ravi.
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of Christian Weiß
Sent: Friday, July 30, 2010 9:32 AM
To: r-help@r-project.org
Subject: [R] Co
Hello,
I am looking for an R function to compute only the largest eigenvalue
(Perron-Frobenius eigenvalue) and its corresponding eigenvector of a
square matrix (in fact, even only of a non-negative matrix). The
function should also be able to deal with very large but sparse matrices.
Any id
On Fri, 9 Apr 2010, Sven Garbade wrote:
Hi list,
can anybody point me to the trick how glm is computing the dispersion
parameter in quasi-poisson regression, eg.
glm(...,family="quasipoisson")?
It isn't. glm() does not need (and does not compute) the dispersion
parameter.
summary.glm will
On Fri, 9 Apr 2010, Sven Garbade wrote:
Hi list,
can anybody point me to the trick how glm is computing the dispersion
parameter in quasi-poisson regression, eg.
glm(...,family="quasipoisson")?
It's the sum of squared Pearson residuals divided by the residual degrees
of freedom. For example:
Hi list,
can anybody point me to the trick how glm is computing the dispersion
parameter in quasi-poisson regression, eg.
glm(...,family="quasipoisson")?
Thanks ®ards, Sven
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-he
Miguel Angel Rodríguez-Gironés Arbolí eeza.csic.es> writes:
>
> Dear Colleagues,
>
> We are using the phylog.gls.fit() function from the R package
> "PHYLOGR" (Diaz-Uriarte R, Garland T:
> PHYLOGR: Functions for phylogenetically based statistical
> analyses. 2007.
[snip]
> ... we would wa
Dear Colleagues,
We are using the phylog.gls.fit() function from the R package "PHYLOGR"
(Diaz-Uriarte R, Garland T: PHYLOGR: Functions for phylogenetically based
statistical analyses. 2007. Available at
[http://cran.r-project.org/web/packages/PHYLOGR/index.html]) to correct for
lack of inde
result <- Reduce("+", unlist(z, recursive=FALSE))
b
On Aug 22, 2009, at 2:03 PM, kathie wrote:
Dear Gabor Grothendieck,
thank you for your comments.
Ive already tried that. but I've got this error message.
Reduce("+",z)
Error in f(init, x[[i]]) : non-numeric argument to binary operato
On Aug 22, 2009, at 1:03 PM, kathie wrote:
Dear Gabor Grothendieck,
thank you for your comments.
Ive already tried that. but I've got this error message.
Reduce("+",z)
Error in f(init, x[[i]]) : non-numeric argument to binary operator
> Reduce("+", c( LL[[1]], LL[[2]] ) )
[,1] [
Hi Kathie,
On Sat, Aug 22, 2009 at 1:03 PM, kathie wrote:
Dear Gabor Grothendieck,
>
>
> thank you for your comments.
>
> Ive already tried that. but I've got this error message.
>
>
> > Reduce("+",z)
> Error in f(init, x[[i]]) : non-numeric argument to binary operator
>
>
> anyway, thanks
>
>
Dear Gabor Grothendieck,
thank you for your comments.
Ive already tried that. but I've got this error message.
> Reduce("+",z)
Error in f(init, x[[i]]) : non-numeric argument to binary operator
anyway, thanks
ps.
> is.matrix(z[[1]][[1]])
[1] TRUE
I guess the reason "Reduce" doesn't wor
See this:
https://stat.ethz.ch/pipermail/r-help/2009-August/208002.html
On Sat, Aug 22, 2009 at 11:41 AM, kathie wrote:
>
> Dear R users,
>
> I have the list as follows;
>
> #--
>
>> z
>
> [[1]]
> [[1]][[1]]
>
> matrix(A)
>
> [[1]][[2]]
>
> matr
Dear R users,
I have the list as follows;
#--
> z
[[1]]
[[1]][[1]]
matrix(A)
[[1]][[2]]
matrix(B)
[[1]][[3]]
matrix(C)
[[2]]
[[2]][[1]]
matrix(D)
[[2]][[2]]
matrix(E)
[[2]][[3]]
matrix(F)
#-
Hi R users:
I want to know if there is any package that makes
the specific computation 2^k factorial designs as in:
George E. P. Box, J. Stuart Hunter and William G. Hunter.
Statistics for Experimenters. Second Edition. 2005.
John Wiley & Sons.
They advice about the misuse of the ANOVA table
in
Thank you very much, yes maybe its worth working on it.
best regards
Andreas
Uwe Ligges wrote:
Andreas Wittmann wrote:
Dear R useRs,
i have the following code to compute values needed for a contour plot
"myContour" <- functio
Andreas Wittmann wrote:
Dear R useRs,
i have the following code to compute values needed for a contour plot
"myContour" <- function(a, b, plist, veca, vecb, dim)
{
tmpb <- seq(0.5 * b, 1.5 * b, length=dim)
tmpa <- seq(0.5 * a
Dear R useRs,
i have the following code to compute values needed for a contour plot
"myContour" <- function(a, b, plist, veca, vecb, dim)
{
tmpb <- seq(0.5 * b, 1.5 * b, length=dim)
tmpa <- seq(0.5 * a, 1.5 * a, length=dim)
z
Hi all,
About how R2WinBUGS computes pD (effective number of parameters), in
the manual it says that pD = var(deviance)/2.
However, I run some data set and find that the reported pD not equal
to var(deviance)/2, but much smaller than that.
Is var(deviance)/2 the actual formular used in R2WinBUGS,
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