2006/1/30, Ionut Florescu [EMAIL PROTECTED]:
I don't know about rownames but
x = 0 gives you a vector of logical values True and false.
If then you do
c(1:length(x)) [x=0]
this gives the positions where the true happened, meaning your vector of
values.
But also returns NA's, if present in
[EMAIL PROTECTED] wrote:
I am creating habitat selection models for caribou and other species with
data collected from GPS collars. In my current situation the radio-collars
recorded the locations of 30 caribou every 6 hours. I am then comparing
resources used at caribou locations to
Martin Julien [EMAIL PROTECTED] writes:
Hi
In mixed-model with lme()
How can I obtain Type II SS or Type III SS for fixed effect?
Thanks
Julien
You don't want that (look up suitable sermon by Bill Venables in the
archives). Single-term Wald tests, however, are available using the
syntax
I'm trying to use predict with a linear mixed-effects logistic
regression model fitted with nlmmPQL from the MASS library.
Unfortunately, I'm getting an error non-conformable arguments in
predict.lme, and I would like to understand why.
I have used the same call to predict with glm models
Michaell Taylor [EMAIL PROTECTED] writes:
I am having trouble installing RMySQL on a clean install of Fedora Core 4 64
bit on a dual dual core machine (that is, two dual core processors). Seems
like the LD_LIBRARY_PATH is incorrect, but I don't seem to have it quite
right yet.
There
Honestly this is the most creative method I've seen.
Thank you for giving me courage to continue exploring R... I had almost
decided to give up feeling that the language is so inconvinient and
counter-intuitive.
On 1/30/06, Gabor Grothendieck [EMAIL PROTECTED] wrote:
Do you mean they are in
No I don't want to adapt them manually by adding , and format them by
hand... that's tedious and daunting...
you cannot just paste it, you have to adapt it either like this
x - matrix( c( 1.2, 3.4, 1.4,
2.3, 3.7, 2.6 ),
nrow = 2, byrow = TRUE)
or
Hello,
I have computed robust regressions with M-estimator using rlm(). The score
function used is psi(x)=c*x/(x^2+c). Distributions are highly concentrated and
have very thick tails.
I have not introduced fixed effects because the important number of
observations could make numerical
You can just use data.frame(). If (using your example) your dataframes
are called first and second, your could
new - dataframe(first$A,second$Z,first$B,second$Y,first$C,second$X...)
followed by
names(new) - c('A','Z','B','Y','C','X')
If you have an enormous number of columns that's a pain,
Michaell Taylor wrote:
I am having trouble installing RMySQL on a clean install of Fedora Core 4 64
bit on a dual dual core machine (that is, two dual core processors). Seems
like the LD_LIBRARY_PATH is incorrect, but I don't seem to have it quite
right yet.
There are a few mentions
Hello, everybody:
I'm experimenting more with Sweave, R, and LyX. There's now an entry
in the LyX wiki on using R, so anybody can do it!
http://wiki.lyx.org/LyX/LyxWithRThroughSweave
Now I notice this frustrating thing. I think I've done everything
possible to make the Design library start up
Thank you very very much for your responses...
How exactly do I vectorize?
One example could be the following, that calculates the sums 1:5,
2:6, 3:7,..., for each of xs[[i]] :
xs - lapply(1:500, function(x) rnorm(1000))
totalsum - list()
sums - list()
first - list()
for(i in
Paul Johnson wrote:
Hello, everybody:
I'm experimenting more with Sweave, R, and LyX. There's now an entry
in the LyX wiki on using R, so anybody can do it!
http://wiki.lyx.org/LyX/LyxWithRThroughSweave
Now I notice this frustrating thing. I think I've done everything
possible to make
Thank you very much!!! It works!.. I will try your philosophy to my script!...
xs - lapply(1:500, function(x) rnorm(1000))
result - lapply(xs, function(.val){
.total - sum(.val) # total sum
.sums - filter(.val, rep(1,5)) # sum 5 consective values
list(total=.total,
ASA == Alexandre Santos Aguiar [EMAIL PROTECTED] writes:
ASA I am new to R and read this list to learn. It is amazing how
ASA frequently new functions pop in messages. Useful and timesaving
ASA functions like subset (above) must be documented somewhere.
ASA Is there a glossary of functions?
Try following this example:
foo - Sys.time()
class(foo)
[1] POSIXt POSIXct
ick - as.numeric(foo)
ick
[1] 1138667199
class(ick)
[1] numeric
class(ick) - class(foo)
ick
[1] 2006-01-30 16:26:39 PST
-Don
At 3:51 PM -0500 1/30/06, David Randel wrote:
I have a column in a data frame
Consider this data frame:
dat-data.frame(id=gl(3,5),time=rep(1:5,3),cm1=rep(c(2,3,4),each=5),cm2=rep(c(2.5,3.5,4.5),each=5),y=rnorm(15))
dat
id time cm1 cm2 y
1 11 2 2.5 -1.0824549
2 12 2 2.5 -0.7784834
3 13 2 2.5 -1.7783560
4 14 2 2.5 0.5056637
5
R2.2 for WinXP, Splus 6.2.1 for HP 9000 Series, HP-UX 11.0.
I am trying to get a handle on why the same lme( ) code gives
such different answers. My output makes me wonder if the
fact that the UNIX box is 64 bits is the reason. The estimated
random effects are identical, but the fixed effects
Since I have not seen a reply to this post, I will offer a comment,
even though I have not used spectral analysis myself and therefore have
you intuition about it. First, from the definitions I read in the
results from, e.g., RSiteSearch(time series power spectral density)
[e.g.,
Using this test data, say:
dd - Sys.Date() + 0:9
fac - gl(5,2)
Try this:
do.call(c, tapply(dd, fac, max, simplify = FALSE))
or if a list result is ok then just
tapply(dd, fac, max, simplify = FALSE)
Another possibility using the as.Date.numeric method in the zoo
package is:
AD == Adrian Dusa [EMAIL PROTECTED] writes:
AD set.seed(5)
AD aa - matrix(sample(10, 15, replace=T), ncol=5)
AD bb - matrix(NA, ncol=10, nrow=5)
AD for (i in 1:ncol(aa)) bb[i, aa[, i]] - c(0, 1, 0)
AD Is there any possibility to vectorize this for loop?
AD (sometimes I have hundreds of columns
[Version française plus bas]
To the R community,
A quick word to announce the publication of my document Introduction
à la programmation en S. It is available in the French section of the
Contributed Documentation page of CRAN.
Many of the documents or books currently available on S-Plus and/or
Thank you very much for providing a concrete, simple, reproducible
example illustrating your question. Without it, it would be much more
difficult for me to understand your question and respond appropriately.
I know this is generally a very hard problem, and I've seen come
On 1/30/06, Patricia J. Hawkins [EMAIL PROTECTED] wrote:
AD == Adrian Dusa [EMAIL PROTECTED] writes:
AD set.seed(5)
AD aa - matrix(sample(10, 15, replace=T), ncol=5)
AD bb - matrix(NA, ncol=10, nrow=5)
AD for (i in 1:ncol(aa)) bb[i, aa[, i]] - c(0, 1, 0)
AD Is there any possibility to
Vincent,
I will be very much interested in the english version of your documentation!
Thanks a lot!
On 1/30/06, Vincent Goulet [EMAIL PROTECTED] wrote:
[Version française plus bas]
To the R community,
A quick word to announce the publication of my document Introduction
à la
Here are a couple of documents that make much the same point (e.g. mean
value imputation is not recommended), and discuss several alternatives.
http://nces.ed.gov/statprog/2002/appendixb3.asp
http://www2.chass.ncsu.edu/garson/pa765/missing.htm
I think we'd need more information on the context
I am lost:
plot(testError, col=red)
lines(testVar, col=black)
Only one plot (the red one) appear on the Window, the black line did not
appear...what's wrong?
Thanks a lot!
[[alternative HTML version deleted]]
__
R-help@stat.math.ethz.ch
Well, one way to do it is
xyplot(y~time|id, data=dat,type='l',
panel=function(x,y,subscripts,...){
panel.xyplot(x,y,subscripts,...)
panel.abline(v=dat[subscripts,cm1])
panel.abline(v=dat[subscripts,cm2])
}
)
Since I don't know what the dataframe 'mergeData'
Thanks Roger, Andy and Dimitris...
though i am familiar with this behaviour **in some cases**, i couldn't
catch - yesterday evening - why it matched with 0.4, and not with 0.3;
of course these numbers are not integers ! but i believed match() deals
with such equalities.
i will have a look at
Michael comtech.usa at gmail.com writes:
plot(testError, col=red)
lines(testVar, col=black)
Only one plot (the red one) appear on the Window, the black line did not
appear...what's wrong?
We can only guess, because you did not supply the data. But I am quite sure,
that the lines-data
Michael wrote:
plot(testError, col=red)
lines(testVar, col=black)
Only one plot (the red one) appear on the Window, the black line did not
appear...what's wrong?
Hang on a second, just let me hack into your machine so I can find out
what 'testError' and 'testVar' are
I'm guessing
Paul Johnson pauljohn32 at gmail.com writes:
echo=F,quiet=T,print=F=
library(Design, verbose=F)
at
But in the output there is still one page of banner information, which
starts like this:
Loading required package: Hmisc
Hmisc library by Frank E Harrell Jr
Type library(help= Hmisc
On Mon, 30 Jan 2006, Peter Dalgaard wrote:
Ionut Florescu [EMAIL PROTECTED] writes:
Actually it does that in my 2.2.1 version as well:
options(digits=20)
8^(1:20)
[1] 8.e+00 6.4004e+01 5.1201e+02
[4] 4.0961e+03 3.27680002e+04
Hi
matrix(colSums(embed(A,3)[1:3,]),3,6, byrow=T)[3:1,]
[,1] [,2] [,3] [,4] [,5] [,6]
[1,]6 33 60 87 114 141
[2,]9 36 63 90 117 144
[3,] 12 39 66 93 120 147
will do it. However I am not sure if it is quicker than your for
loop.
HTH
Petr
On 30 Jan 2006
On 31-Jan-06 Michael wrote:
I am lost:
plot(testError, col=red)
lines(testVar, col=black)
Only one plot (the red one) appear on the Window, the black line did
not
appear...what's wrong?
Thanks a lot!
Check the ranges of values of your two variables (in both x and y
directions in
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