Dear all,
I'm having trouble interpolating a number of gridded datasets that I have. I'm
quite new to R so any help/advice that can be offered would be much appreciated!
Firstly I'll describe my dataset. The data is a grid of the planet at 1 degree
spatial resolution, with each grid cell
Hi,
You seem to have a glitch in one file,
testread12=read.table(Test100.txt, head = T)
str(testread12) # Column131 is converted to a factor
# $ Column131: Factor w/ 2920 levels --,-0.000122393,..
combining the second data set with this one will convert the new data
into factor for this
I am using R on a Windows XP professional platform.
The following code is part of a bigger one
CODE
press=function(y,x){
library(qpcR)
models.press=numeric(0)
cat(\n)
dep=y
print(dep)
indep=log(x)
print(indep)
yfit=dep-PRESS(lm(dep~indep))[[2]]
cat(\n yfit\n)
Both from the code and the error message it appears that you are
creating character matrices and unrealistically expecting a function
designed for numeric input to accept those as arguments.
?sprintf
It appears you are hoping that sprintf gets you something you desire,
but to my eyes it
I was suggested to install two tar-red and gzip-ped packages that are not part
of CRAN or BioConductors yet.
I read the R manual about Administration and could only find a good description
of how to install packages
not canonically included in CRAN repository, on UNIX systems.
I work on
For instance, I am trying to run Roxygen on:
require( zoo ) # needed for time series
setClass( zoo ) # lets S4 know about S3 class so we can use as an
argument
setClass( myClass, representation( .zoo=zoo ), prototype( 0,
as.Date(1970-01-01) ))
When I run this code through
Dear All,
I've been using step function to find me the best model.this basically works
by using AIC score fucntion that is implemented on step(). The problem I'm
facing with lots of variables on the model for example :
step(lm(x1~x2,x3,x4,..x13)) sometimes gives me a warning message which
Hi!
Take a look at this page:
http://fawn.hsu-hh.de/~steuer/rpage.html
The package you want to install ist called
R-base-devel-*.rpm
These packages are provided in opensuse's build service.
Hope that helps
Detlef
On Sat, 20 Jun 2009 21:52:56 -0400
R_help Help rhelp...@gmail.com wrote:
Hi,
Thank-you all for your reply. It turns out that there were both #
characters and unbalanced quotes in the character fields that were
creating problems for read.table.
Putting in the options quote= and comment= in the read.table
statment fixes the problem.
On Fri, Jun 19, 2009 at 9:51 PM, jim
All:
Though I am fairly new to R, I am trying to work my way through J Oksanen's
Incidence Function Model in R and can't get past some error with my glm
arguments. I'm getting through
attach(amphimedon_compressa)
plot(x.crd,y.crd,asp=1,xlab=Easting,ylab=Northing,pch=21,col=p+1,bg=5*p)
Unfortunately my actual function is a bit more complicated than
ce=ce+be and does many transformations on the original vectors.
Maybe something like this better conveys what I am trying to do:
functM - function(eh,be,period,endPeriod){
period - period+1
ce - eh+be
de -
Endy BlackEndy wrote:
I am using R on a Windows XP professional platform.
The following code is part of a bigger one
CODE
press=function(y,x){
library(qpcR)
models.press=numeric(0)
cat(\n)
dep=y
print(dep)
indep=log(x)
print(indep)
Endy BlackEndy wrote:
I am using R on a Windows XP professional platform.
The following code is part of a bigger one
CODE
press=function(y,x){
library(qpcR)
models.press=numeric(0)
cat(\n)
dep=y
print(dep)
indep=log(x)
print(indep)
Stavros Macrakis wrote
[...]
programming languages (including R). I don't know whether R's sum function
uses this technique or some other (e.g. Kahan summation), but it does manage
to give higher precision than summation with individual arithmetic
operators:
sum(c(2^63,1,-2^63)) = 1
Extend it like this:
Try this:
f - function(d, endPeriod) with(d, {
period - period + 1
ce - eh + be
de - (eh + be)^2
ee - ifelse(ce de, de, ce)
eh - ifelse(period endPeriod, ce, eh)
data.frame(eh,
At 07:40 21.06.2009, J Dougherty wrote:
[...]
There are other ways of regarding the FET. Since it is precisely
what it says
- an exact test - you can argue that you should avoid carrying over any
conclusions drawn about the small population the test was applied to and
employing them in a
On Jun 21, 2009, at 2:47 PM, steve kimble wrote:
All:
Though I am fairly new to R, I am trying to work my way through J
Oksanen's
Incidence Function Model in R and can't get past some error with
my glm
arguments. I'm getting through
attach(amphimedon_compressa)
Hi,
I have a array like this
data:
1 5
2 2342
3 33
and another
data1:
1 6
2 5
3 7
when I do rbind(data,data1)
I get not what I want
they become
1 5
2 2342
3 33
101 6
102 5
103 7
but I want to make the index as increasing one by one.
like
1 ..
2 ..
3 ..
4 ..
5 ..
6 ..
So what command I
because the index in the result of rebind is not increasing one by one,
how can I deal with row one after another
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do
You need to provide a reproducible example. At least provide an 'str' of
your data and preferably the output of 'dput'. I am not sure what you data
looks like.
works fine for me when using matrices:
data
[,1]
[1,]5
[2,] 2342
[3,] 33
data1
[,1]
[1,]6
[2,]5
[3,]7
You need to indicate what the data is. You still reference the rows
sequentially regardless of what that first column of your output is saying.
PLEASE do read the posting guide
http://www.R-project.org/posting-guide.htmlhttp://www.r-project.org/posting-guide.html
and provide commented, minimal,
On Sat, Jun 20, 2009 at 9:13 AM, nmsetnm...@netcourrier.com wrote:
Hello,
I'm plotting an xyplot where a continuous var recorded every min is plotted
on y, and time expressed as HH:MM:SS on x, as follows :
xaxis=list(tick.number=12,rot=90)
lst=list(x=xaxis)
xyplot(upt$LOAD_1 ~ upt$TIME,
# I have a function that takes a few vectors manipulates them and then
outputs a matrix of results:
funct1 - function(eh,be){
ce - eh+be
data.frame(eh,be,ce)
}
ones - c(1,1,1)
twos - c(2,2,2)
funct1(ones,twos)
# I would like to iterate it and save the results
For measures of association between two variables with two values each,
Cramer's V and Yule's Q are useful statistics. Look into this thread, for
example: http://markmail.org/message/sjd53z2dv2pb5nd6
To get a grasp from plotting (sometimes), you may use the jitter function in
the plot...
Any way to tell Roxygen to ignore a block of code? It is generating an
unwanted .Rd file.
I've been searching for hours for an example, scouring documentation, but no
luck...
Thanks.
- Ken
--
View this message in context:
Hi Ken,
I have been using R for a while. Recently, I have begun converting my
package into S4 classes. I was previously using Rdoc for documentation.
Now, I am looking to use the best tool for S4 documentation. It seems that
the best choices for me are Roxygen and Sweave (I am fine with
Try Reduce:
f - function(d, incr = 1) with(d,
data.frame(eh = ce, be, ce = ce + be, period = period + incr))
d - data.frame(ce = ones, be = twos, period = 0)
Reduce(f, init = d, x = rep(1, 4))
Reduce(f, init = d, x = rep(1, 4), accumulate = TRUE)
On Sun, Jun 21, 2009 at 9:06 AM,
Answering my own question: if I explicitly garbage collecte before the
benchmark then 'index' always wins, which probably also answers the
original question.
v-rep(1:1000,1:1000); x-5; gc(); benchmark(replications=200,
columns=c(test,elapsed), order=elapsed, which=length(which(x==v)),
I have been using R for a while. Recently, I have begun converting my
package into S4 classes. I was previously using Rdoc for documentation.
Now, I am looking to use the best tool for S4 documentation. It seems that
the best choices for me are Roxygen and Sweave (I am fine with tex).
Are
If one puts the gc() call prior to the expressions themselves, one
gets consistently ... different results:
library(rbenchmark)
v-rep(1:500,1:500); x-5; benchmark(
which= c(gc(),length(which(x==v))), index= c(gc(),
length(v[v==x])), sum= c(gc(), sum(v==x)),
replications=200,
On 2009.06.20 16:04:21, Alexandru T Codilean wrote:
Dear All,
I have a data set with the following structure:
[A], [a], [B], [b]
where [A] and [B] are measurements and [a] and [b] are the associated
uncertainties. I produce [B]/[A] vs. [A] plots in R and would like to
show
Hello,
I have been using a very simple rbind approach (simple enough for me to
understand) to combine data files within R.
It seems to work fine, but then generates warning messages for reasons that
I can't begin to understand. The text below shows the issue.
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