Hi Matthias.
The first thing I notice is that the vector r:
r<-c(1.1717118,1.1605215,1.1522907,1.1422830,1.1065277,1.1165451,
1.1163768,1.1048872,1.0848836,1.0627211,1.0300964,1.0296879,
1.0308194,1.0518188,1.0657229,1.0685514,1.0914881,1.1042577,
1.1039351,1.0880163)
doesn't contain the value
You need to provide reproducible data. What does the file contain? Why
are you using 'sep=' when reading fixed format. You might be able to
attach the '.txt' to your email to help with the problem. Also you did not
state what the differences that you are seeing. So help us out here.
Jim Holt
> On Jun 13, 2017, at 4:10 PM, Rolf Turner wrote:
>
> On 14/06/17 08:46, matthias worni wrote:
>> Hey
>> This should be a rather simple quesiton for some of you. I want to make
>> some progress in looping...
>> I have the vector r, which contains single values --> see below:
>> r
>> [1] 1.1717
On 14/06/17 08:46, matthias worni wrote:
Hey
This should be a rather simple quesiton for some of you. I want to make
some progress in looping...
I have the vector r, which contains single values --> see below:
r
[1] 1.1717118 1.1605215 1.1522907 1.1422830 1.1065277 1.1165451 1.1163768
1.1048
Hey
This should be a rather simple quesiton for some of you. I want to make
some progress in looping...
I have the vector r, which contains single values --> see below:
r
[1] 1.1717118 1.1605215 1.1522907 1.1422830 1.1065277 1.1165451 1.1163768
1.1048872 1.0848836 1.0627211
[11] 1.0300964 1.02
Hi all,
I have a file of average SWE observations for 40 years at over 4,000 points
and am attempting to do a spatiotemporal analysis of the data using PCA,
much like this paper did using snow depth:
http://journals.ametsoc.org/doi/pdf/10.1175/1520-0442%281998%29011%3C0856%3ATCIRWS%3E2.0.CO%3B2
I
Hi all,
I am using R to extract data on a regular basis.
However, sometimes using the same script and the same data I am
getting different observation.
The library I am using and how I am reading it is as follows.
library(stringr)
namelist <- file("Adress1.txt",encoding="ISO-8859-1")
Name <- re
On Tue, 13 Jun 2017, Dimitrie Siriopol via R-help wrote:
I am trying to use the CART in a survival analysis. I have three variables of
interest (all 3 ordinal - x, y and z, each of them with 5 categories) from
which I want to make smaller groups (just an example 1st category from X
variable w
>
> On 13 Jun 2017, at 23:05, Bond, Stephen wrote:
>
> Hi useRs,
>
> I am running a foreach loop and hoped to get a small message when it hits a
> multiple of 1000, but it does not work.
>
>p <- foreach(i=1:1, .combine='c') %dopar% {
>if(i%%1000==0) print(i)
>
Hi useRs,
I am running a foreach loop and hoped to get a small message when it hits a
multiple of 1000, but it does not work.
p <- foreach(i=1:1, .combine='c') %dopar% {
if(i%%1000==0) print(i)
sqrt(i)
}
What is the proper way to do it.
Thanks everybo
If you don't get a prompt reply here, you might do better posting this
on the r-sig-mixed-models list (for obvious reasons).
Cheers,
Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom
Is there a difference between I(x*y) and I(y*x) ?
I have a call to lmer that results in this complaint:
Error in is.alpha2.subordinate * ~z.min.co.res :
non-numeric argument to binary operator
when I change this line:
I(is.alpha2.subordinate*z.min.co.res)+
to this:
I(z.min.co.res*is.alph
1. Please read and follow the posting guide below. Your post does not
meet the guidelines.
2. Search before posting!
e.g. on rseek.org: "Regression trees survival analysis"
in which you will find:
https://cran.r-project.org/web/views/MachineLearning.html
-- Bert
Bert Gunter
"The trouble with
I am trying to use the CART in a survival analysis. I have three variables of
interest (all 3 ordinal - x, y and z, each of them with 5 categories) from
which I want to make smaller groups (just an example 1st category from X
variable with the 2nd and 3rd categories from the Y category and 2, 3
Hi Duncan
Thank you very much for your help.
The function model$gam is correct; it applies to gamm4 as well.
I believe that it is the smooth term the reason that the plots from lattice are
not the same as the plots from the plot(model$gam) but at least I can get the
smooth line and the confiden
Hello all,
I'd like to calculate the mean correlation within a cluster and understand if
it's significantly >0. I'm using packages 'geomorph' and 'paleomorph'.
#Simulate an array A <- array ( rep ( 1 : 36 , by = 4 ), dim = c ( 12 , 3 , 4
)) #Load 'geomorph' package and superimpose coordinate
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