On Jan 6, 2013, at 04:00 , Pfeiffer, Steven wrote:
> Hello,
> For an experiment, I selected plots of land within a forest either with
> honeysuckle or without honeysuckle. Thus, my main factor is fixed, with 2
> levels: "honeysuckle present"(n=11) and "honeysuckle absent"(n=8).
>
> Within each
On 1/6/2013 12:45 AM, peter dalgaard wrote:
On Jan 6, 2013, at 04:00 , Pfeiffer, Steven wrote:
Hello,
For an experiment, I selected plots of land within a forest either with
honeysuckle or without honeysuckle. Thus, my main factor is fixed, with 2
levels: "honeysuckle present"(n=11) and "honey
Hi Jim,
The last question:
I changed my function robustm () to have as output the scatter matrix and
the data to re-enter into the process and I used as suggested you "while
do", and seems to work without errors.
iterate.robustm<-function(x,z) {
b<-robustm(x,z)
Hi A.K
Regarding my question on comparing normal/ obese/overweight with blood
pressure change, I did finally as per the first suggestion of stacking the
data and creating a normal category . This only gives me a obese not obese
14, but when I did with the wide format hoping to get a
obese14,norm
Hello everyone,
I have been spending many hours on a seemingly simple portfolio optimization
problem using the package fPortfolio.
My optimization problem is slightly different than a standard one such that I
have a known set of asset returns. My problem is how to collect this
information int
Please read the posting guide and use a sensible subject line, tell us
about the R version you are using, and add a *reproducible* example.
We get:
Error in nls(npe ~ SSgompertz(npo, Asym, b2, b3), data = f, control =
nls.control(maxiter = 500)) :
object 'f' not found
Best,
Uwe Ligges
On
On 04.01.2013 17:10, catalin roibu wrote:
Dear R users,
I want to group the d values in classes. If I use this script I have a
problem.
classes <- function(x, n){
s <- seq(0, ceiling(max(x)), by = n)
factor(n*findInterval(x, s), levels = s)
}
z<-sapply(tapply(t$d,t$plot,function(x) classe
On 04.01.2013 19:22, rydood wrote:
I am having trouble predicting new data with a model created from package
mboost:
mb1<-glmboost(as.formula(formula1),data=data_train,control=boost_control(mstop=400,nu=.1))
f.predict<-predict(mb1,newdata=data_train)
Error in scale.default(X, center = cm, s
On Jan 6, 2013, at 09:45 , peter dalgaard wrote:
>
> Just avoid things like Type-III sums of squares (base R won't do them, but
> popular add-ons will) because they get it wrong when cell counts are unequal.
That might be a bit unfair. Type-III methodology has its proponents, I'm just
not one
I have a raster file of the whole world and coordinates (latitude and
longitude). I want to plot the coordinates on the raster file by showing the
densitiy of the coordinates per raster pixel by using colours. So in the end
I can see e.g. dark read at places in the world where there are high
concen
Hi,
I am not very familiar with the geese/geeglm(). Is it from library(geepack)?
Regarding your question:
"
Can you tell me if I can use the geese or geeglm function with this data
eg: : HIBP~ time* Age
Here age is a factor with 3 levels, time: 2 levels, HIBP = yes/no.
>From your original data:
For more details about floating-point:
http://docs.oracle.com/cd/E19957-01/806-3568/ncg_goldberg.html
2013/1/5 peter dalgaard
>
> On Jan 5, 2013, at 20:30 , Rolf Turner wrote:
>
> > On 01/06/2013 07:42 AM, David Arnold wrote:
> >> Hi,
> >>
> >> Can someone explain this:
> >>
> >>> options(digit
Dear Peter,
Thank you for the clarification, since one (I hope) popular add-on that
computes type-II and -III tests for repeated-measures designs is the Anova()
function in the car package.
The type-II tests are, in my opinion, preferable, because they are maximally
powerful, e.g., for main effe
Dear all:
Plan 1:
I want to do serval t-test means for different variables in a loop ,
so I want to add all results to an object then dump() them to an
text. But I don't know how to append T-test result to the object?
I have already plot the barplot and I want to know an elegant way to
report ra
Thank you，it is really helpful everytime.
I didn't provide any example data because I thought it is just a
question of how to report t.test() result in R.
However,as you say,it is better to show more details for finding an elegant way
In fact I generate a 3-dimension array like that:
str(a)
num
Hi, how are you?
I have an attached file (StationIDs) that lists 74 observation sites
that I need to process using the EGRET/WRTDS R-package. For each site, I
need to load information into the Sample, INFO, and Daily fields.
The "sitenumber" in the following code refers to one of the 74
observati
Hi,
You didn't provide any example data. So, I am not sure whether this helps.
set.seed(15)
dat1<-data.frame(A=sample(10:20,5,replace=TRUE),B=sample(18:28,5,replace=TRUE),C=sample(25:35,5,replace=TRUE),D=sample(20:30,5,replace=TRUE))
dat2<-dat1[,-1] # I forgot to paste this line
res<-lapply(la
Hi all,
I have read through the archives, but can't find a solution to this problem.
I need the text direction on "dependent B", plotted in margin 4, to go
top to bottom (opposite what it is now). Here's some sample code:
#plot with mtext example
par(mgp = c(2,1,0), mfrow=c(2,2), las=1, mar
HI,
I tried to create an example dataset (as you didn't provide the data).
set.seed(25)
a<-array(sample(1:50,60,replace=TRUE),dim=c(2,10,3))
dimnames(a)[[1]]<-c("13%","21%")
dimnames(a)[[2]]<-paste("TWF2H",101:110,sep="")
dimnames(a)[[3]]<-c("EW.INCU","EW.17.5","EMW")
str(a)
# int [1:2, 1:10, 1:3
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