Jack B. Arnold wrote:
> Dear Tom,
>
> Looking forward to your book. "Psychologists and students" clearly need
> all the encouragement to use R that they can get. I have been using it
> for a couple of years now, and find, that for most purposes, it is just
> a little harder to get into than t
Hello,
I have a several time series, which I would like to check for their best
fitted Arima model (I am checking for the lowest aic value).
Which lets me raise two questions:
1) is there are more efficient way, than using 6 for-loops?
2) sometimes the system cannot calculate with given paramete
> But how is that different from just a 3-way ANOVA with age, diagnosis,
> and gender as the the three effects? Isn't ANCOVA a fundamentally
> different model?
> Thanks,
> Sasha
ANCOVA is a linear model with both factors and continuous variables
on the right-hand side of the model formula. In p
Please visit the R site http://www.r-project.org/ and search the mailing
list for "paste expression" We discussed the topic recently. The "trick"
is that you don't paste expressions, you make an expression containing
paste.
Charles Annis, P.E.
[EMAIL PROTECTED]
phone: 561-352-9699
eFax: 614-
Try bquote:
y.hat <- sigma.hat <- 1.1
plot(1)
lab <- bquote(hat(y) == .(y.hat) * "," ~ hat(sigma)^2 == .(sigma.hat))
text(1, 1, lab, pos = 4)
On 8/23/06, Jeff D. Hamann <[EMAIL PROTECTED]> wrote:
> I can't believe I'm having such a hard time with this and I haven't been
> able to find out how to
I can't believe I'm having such a hard time with this and I haven't been
able to find out how to solve this...
lab <- expression( paste( hat(v),
as.character(round(y.hat,2)), ",",
hat(sigma)^2, as.character(sigma.hat)) )
text( x=pt$x+2, y=pt$y,labels=lab )
## the text should be \hat{y} =
I want to replace one row with other information in the dataframe. For
example:
> cb04.full[1:5,]
tag sp gx gy dbh codes status branch species lifestyle *family*genera
1 10101 COMA 1.64 1.54 1.2 10111 alive 0毛榛 COMA *COMA*
COMA
2 10102 COMA 2.05 2.45 1.5 10111 a
Hi -
I am doing an analysis using panel data methods, particularly what
economists call "fixed effects". It can easily be done in R through
the inclusion of factors in an lm formula. However, when the number of
groups is excessive (in my case 2000+) it is much more efficient to
demean the data by
Dear list,
Is there any way to load a local data file when connected to a remote
machine via ESS?
Thanks!
Manuel
__
R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-projec
Hi,
I am planning on using classification trees to build a predictive model for
data which includes a random variable. I intend to use the R functions 'rpart'
(and potentially also 'randomForest' and 'bagging').
I have a data set with 390 data points. The response variable is binary. There
ar
A new version 1.9-5 of the package `spatstat'
has been uploaded to CRAN.
What it is:
--
spatstat is a package for analysing spatial data, mainly Spatial Point
Patterns.
What's in it:
Functions for exploratory data analysis, model-fitting, simulation,
spatial sampling, mode
On 8/23/2006 5:15 PM, Gaspard Lequeux wrote:
> Hej,
>
> When exporting a image from rgl, the following error is encountered:
>
>> rgl.postscript('testing.pdf', fmt="pdf")
> RGL: ERROR: can't bind glx context to window
> RGL: ERROR: can't bind glx context to window
> Warning messages:
> 1: X11 pro
On 8/23/2006 4:13 PM, Gaspard Lequeux wrote:
> Hej,
>
> When plotting triangles with rgl.triangles and setting the axes afterwards
> with decorate3d(aspect=TRUE), the axes get the color used for the last
> triangle plotted.
>
> Example:
>
> rgl.triangles(c(1,2,3),c(1,2,5),c(1,3,2),col="#55FF55
Hi.
Does anyone know whether the following error is a result of a bug or a
feature?
I can eliminate the error by making ML=F, but I would like to see the
values of the cut-points and their variance. Is there anything that I
can do?
tmp.vec<-c(0, 0, 0 , 0 ,0 , 1, 0, 2, 0 , 0, 5 ,5 ,
Please contact the package maintainer.
-- Bert Gunter
Genentech Non-Clinical Statistics
South San Francisco, CA
"The business of the statistician is to catalyze the scientific learning
process." - George E. P. Box
> -Original Message-
> From: [EMAIL PROTECTED]
> [mailto:[EMAIL PRO
Hej,
When exporting a image from rgl, the following error is encountered:
> rgl.postscript('testing.pdf', fmt="pdf")
RGL: ERROR: can't bind glx context to window
RGL: ERROR: can't bind glx context to window
Warning messages:
1: X11 protocol error: GLXBadContextState
2: X11 protocol error: GLXBad
Hej,
When plotting triangles with rgl.triangles and setting the axes afterwards
with decorate3d(aspect=TRUE), the axes get the color used for the last
triangle plotted.
Example:
rgl.triangles(c(1,2,3),c(1,2,5),c(1,3,2),col="#55FF55")
decorate3d(aspect=TRUE)
Using
decorate3d(aspect=TRUE,col=
Hello all,
I am new to r as well as wavlets. The following is a times series from a
bond portfolio I have uploaded from a text file.
Bond1 <- scan("C:.../UploadR2.txt")
I am trying to decompose the portfolio return using wavelets. My goal is to
find out the wavlet variance and average at eac
Hi All,
I'm trying to figure out the cumulative incidence curve in R in some
limited time. I found in package "cmprsk", the command "plot.cuminc" can
get this curve. But I noticed that there is no mark for the censored
time there, comparing with the KM curve by "plot.survfit". Here are my
codes
After I updated my R from 2.2.0 to 2.3.1, it is working fine now. Thanks!
Mike
On 8/23/06, Prof Brian Ripley <[EMAIL PROTECTED]> wrote:
>
> Your example works for me without any error messages in R 2.3.1 with the
> current (uncredited) MASS package 7.2-27.1, including giving about 20 'ok
> here.'.
You could also look at p.arrows in sfsmisc package which is
entirely in R.
On 8/23/06, B. Chasco <[EMAIL PROTECTED]> wrote:
> There is a function called arrows() which is an .Internal function. How
> difficult is it to modify that function to return the xy coordinates for
> the line "segments" th
Hi !
I am trying to get at the covariance of the predictions of a linear model.
Suppose the we have:
> x<-runif(1000)
> y<-2 + 25x*x +rnorm(1000)
> lm1 <-lm(y~x, data = data.frame(y = y, x=x))
> x.pred <-runif(10)
> y.hat <- predict(lm1, newdata = data.frame(x=x.pred))
I was wondering how to g
On Wed, 23 Aug 2006, Damien Moore wrote:
>
> Thomas Lumley < [EMAIL PROTECTED] > wrote:
>
>> I have written most of a bigglm() function where the data= argument is a
>> function with a single argument 'reset'. When called with reset=FALSE the
>> function should return another chunk of data, or NUL
On Wed, 23 Aug 2006, B. Chasco wrote:
> There is a function called arrows() which is an .Internal function. How
> difficult is it to modify that function to return the xy coordinates for
> the line "segments" that make up the arrowhead?
That depends on your 'core competencies'. You have the s
Your example works for me without any error messages in R 2.3.1 with the
current (uncredited) MASS package 7.2-27.1, including giving about 20 'ok
here.'.
Did you heed the advice in the posting guide to update (as well as to tell
us the versions of things you were using)? Probably not (as you
There is a function called arrows() which is an .Internal function. How
difficult is it to modify that function to return the xy coordinates for
the line "segments" that make up the arrowhead?
Brandon Chasco
University of Washington
ph (206) 221-6768
___
Hello,
I have two regression equations, one predicts number of interactions from
people-a and the other predicts number of interactions from people-b. I am
summing the number of interactions to get the combined number of interactions.
How do I calculate the combined standared error?
Philip
OK, now that I've worked through Venebales and Ripley and a few other
sources, I can see more than one way of attacking a problem I expect
to be facing soon: a repeated-measures MANCOVA with more than one
X-factor.
But that got me wondering how the people who've been playing with R
longer than I h
On Wed, 23 Aug 2006, Frank E Harrell Jr wrote:
> Thomas Lumley wrote:
> > On Wed, 23 Aug 2006, Damien Moore wrote:
> >
> > > Thomas Lumley wrote:
> > >
> > > > No, it is quite straightforward if you are willing to make multiple
> > > > passes
> > > > through the data. It is hard with a single pas
Thomas Lumley < [EMAIL PROTECTED] > wrote:
>I have written most of a bigglm() function where the data= argument is a
>function with a single argument 'reset'. When called with reset=FALSE the
>function should return another chunk of data, or NULL if no data are
>available, and when called with
Thomas Lumley wrote:
> On Wed, 23 Aug 2006, Damien Moore wrote:
>
>> Thomas Lumley wrote:
>>
>>> No, it is quite straightforward if you are willing to make multiple passes
>>> through the data. It is hard with a single pass and may not be possible
>>> unless the data are in random order.
>>>
>>> F
On Wed, 23 Aug 2006, Damien Moore wrote:
>
> Thomas Lumley wrote:
>
>> No, it is quite straightforward if you are willing to make multiple passes
>> through the data. It is hard with a single pass and may not be possible
>> unless the data are in random order.
>>
>> Fisher scoring for glms is just
Thanks Bill and Simon. I wrote a simpler function to test and found out it
was stepAIC which causes error, and I still don't know how to solve it.
Check out this simple function:
myfun<-function(k){
xx<-mvrnorm(100,rep(0,10),diag(1,10),empirical=TRUE)
colnames(xx)<-paste("x",1:10,sep='')
py
Thomas Lumley wrote:
> No, it is quite straightforward if you are willing to make multiple passes
> through the data. It is hard with a single pass and may not be possible
> unless the data are in random order.
>
> Fisher scoring for glms is just an iterative weighted least squares
> calculat
Hello!
I am running R-2.3.1-i386-1 on Slackware Linux 10.2. I am a former matlab user,
moving to R. In matlab, via the cftool, I performed nonlinear curve fitting
using the method "nonlinear least squares" with the "Trust-Region" algorithm
and not using robust fitting. Is it possible to perform
With lattice graphics:
library(lattice)
d1 <- rnorm(100)
d2 <- runif(100)
densityplot(~ d1 + d2, auto.key = TRUE)
On 8/23/06, Antje <[EMAIL PROTECTED]> wrote:
> Hello,
>
> I was wondering if I can plot two curves I get from "density(data)" into
> one plot. I want to compare both.
> With the follo
Hello,
Thank you very much for your response!
However, I still do not understand how this works. I would like to
adjust the factors (diagnosis and gender) for the covariate (age), so
you are saying I should use:
aov.out <- aov(response ~ age + diagnosis*gender, data)
or
aov.o
Hello,
I'm trying to install odrpack (http://www.netlib.org/odrpack/) on my
ubuntu linux system. That is a fortran package which I need to fit a
circle to 2-dim data points (if someone knows a simpler package for
that task, please tell me).
For installing odrpack, I need a utility called fsplit,
On Aug 23, 2006, at 8:08 AM, [EMAIL PROTECTED] wrote:
> I have constructed histograms of various variables in my dataset.
> Some of them are negatively skewed, and hence need data
> transformations applied. I know that you first need to reflect the
> negatively skewed data and then apply a
a simple reflection (on the y-axis) of x is -x, but you have to ensure
that there are only nonnegative numbers if you want to use the log
transformation. So you should reflect on a postive number z greater than
abs(min(x)), if min(x)<0. This is done by z-x.
Why don't you simply shift your dat
Hi
This is a little bit more precise. My sugeestion works with unordered
data and finds row index for second item lower then a threshold.
which(diff(cumsum(diff(data<3.5)==1)<2)!=0)+2
However with ordered data you need to slightly modify it
which(diff(cumsum(diff(data<3.5)!=0)<2)!=0)+2
I bet
[EMAIL PROTECTED] wrote:
> Hi,
>
> This problem may be very easy, but I can't think of how to do it. I have
> constructed histograms of various variables in my dataset. Some of them are
> negatively skewed, and hence need data transformations applied. I know that
> you first need to reflect
On 8/23/2006 8:08 AM, [EMAIL PROTECTED] wrote:
> Hi,
>
> This problem may be very easy, but I can't think of how to do it. I have
> constructed histograms of various variables in my dataset. Some of them are
> negatively skewed, and hence need data transformations applied. I know that
> you
I'm new to R myself, but am wondering whether the t() (transpose) function
would work?
> hist(t(Lsoc))
Jon
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of
[EMAIL PROTECTED]
Sent: 23 August 2006 13:08
To: r-help@stat.math.ethz.ch
Subject: [R] negatively s
Hi,
This problem may be very easy, but I can't think of how to do it. I have
constructed histograms of various variables in my dataset. Some of them are
negatively skewed, and hence need data transformations applied. I know that
you first need to reflect the negatively skewed data and then a
Jon Minton wrote:
> Hi,
>
>
>
> I'm new to R so this might be a little basic for enlightened people like
> yourselves...
>
>
>
> I have quarterly British Labour Force Survey (Local Area) data from 1992 to
> present in .tab format* in folders running from 01 (for the first time
> period) to 56
Why are the results not reliable?
From: ESCHEN Rene [mailto:[EMAIL PROTECTED]
Sent: Wednesday, August 23, 2006 3:48 AM
To: Spencer Graves; r-help@stat.math.ethz.ch
Cc: Doran, Harold
Subject: RE: [R] Random structure of nes
Thank you both very much.
It works!
__
R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reprodu
On Wed, 23 Aug 2006, [EMAIL PROTECTED] wrote:
> Hi,
>
> search on web indicates that R also includes a hist method on POSIXct
> vectors.
> methods(hist)
[1] hist.Date* hist.default hist.POSIXt*
Non-visible functions are asterisked
so almost (objects of class POSIXct inherit from class POS
try this:
x1 <- rnorm(1000)
x2 <- rnorm(1000)
d1 <- density(x1)
d2 <- density(x2)
plot(range(d1$x, d2$x), range(d1$y, d2$y), type = "n",
xlab = "x", ylab = "Density")
lines(d1, col = "red")
lines(d2, col = "blue")
I hope it helps.
Best,
Dimitris
Dimitris Rizopoulos
Ph.D. Student
Bio
Hello,
I was wondering if I can plot two curves I get from "density(data)" into
one plot. I want to compare both.
With the following commad, I just get one curve plotted:
plot( density(mydata) )
Sorry for this stupid question but I could not find a solution until now...
Antje
Hi,
search on web indicates that R also includes a hist method on POSIXct
vectors.
My (perhaps too unexperienced) approach below yields an error.
Could somebody give me a hint what's wrong ?
Peter
> str(samples)
`data.frame': 7500 obs. of 1 variable:
$ DateTime:'POSIXct', format: chr "2
Hi there
Is there a function in R that will take a distance matrix and print it to file
as follows:
Object1 Object2 67.99
Object1 Object3 90.44
etc.
Any help/suggestions/references I should look up much appreciated.
[[alternative HTML version deleted]]
___
Hi,
I'm new to R so this might be a little basic for enlightened people like
yourselves...
I have quarterly British Labour Force Survey (Local Area) data from 1992 to
present in .tab format* in folders running from 01 (for the first time
period) to 56 (for the most recent).
i.e. my dir
Hi
I am not sure what you really want. If you try to preserve first part
of your objects just exclude them from operation e.g.
data[-(1:5),] will exclude first five rows from your dataframe.
However it is unclear what you want to do next. Instead of three
items you want only add one different?
The output of the suggested lmer model looks very similar to the output of aov,
also when I ran the model on the dataset I want to use. Thank you very much for
the suggestion, this appears to solve my problem to a great extend.
However, one of my response variables is survival of my plants, whi
56 matches
Mail list logo
