R supports a wide range of data transfer methods, Petr... you know for example
that if you export data from Excel in CSV format then you can import it to R,
yet this solution does not satisfy all users in all cases. What expectations do
you have?
Why don't you do some legwork and identify what
Hallo all
Does anybody know if R could be used directly with FactoryTalk Historian
programme from Rockwell automation.
It is probably possible to use Excel as interface but I would prefer not to.
Best regards.
Petr Pikal
Osobn? ?daje: Informace o zpracov?n? a ochran? osobn?ch ?daj? obchodn?ch
Dear All,
Thank you for your advice.
I have looked at the plotrix package and with what I gathered, I
tinkered with the code below and obtain the attached graph:
oolt<-read.table("QUERY2",col.names=c("Lat","Lon"))
latlim<-c(20,45)
lonlim<-c(-180,180)
latbreaks<-seq(latlim[1],latlim[2],by=5)
lonb
Hi Aveek,
1. This is an "all-text" mailing list. Your attachment did not come
through.
You can check out the posting guide (see the link at the bottom of your
email)
and/or
use dput(...) on your structures and paste them into your email so
that members of the list can try to reproduce
Hi All,
I am facing an issue with an optimization problem which I am trying to solve
using NlcOptim package in R. I have tried reaching out to the package
maintainer but not received any response, hence posting this here.
Below is the code snippet I am using:
#Optimization
obj_F <-
Thanks a lot David for this extended answer
The aim is to say: if simulated vs emprical correlate one by one, the sum
of both should correlate also
I want to be sure that I understood correctly:
What you have done
1) building the model ( the fittingness) according empirical vs simulated
value and
Hi Ogbos,
I have been off the air for a couple of days. Look at the color.legend
function in the plotrix package.
Jim
On Tue, Dec 11, 2018 at 12:39 PM Ogbos Okike wrote:
>
> Dear Jim,
> I am still having trouble with the colour code. I await your help when
> you are less busy.
>
> Thank you.
> Be
I am running a small simulation, and getting very different run times when I
use different versions of R.
Two set-ups using the same machine (MacBook Pro 2013 vintage)
1. R version 3.1.3 running on system OS X 10.9.5
> system.time(source("simulationR-R.R"))
user system elapsed
3.890 0
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