Hi Jim
2014-07-19 8:25 GMT-03:00 Jim Lemon :
>
> Hi Vero,
> I think this does what you want, even though it doesn't do it the way
> you describe above.
>
> cla<-runif(506)+
> rep(c(seq(1,3,length.out=23),seq(3,1,length.out=23)),11)
> obs_time<-paste(rep(1:11,each=46),rep(1:46,11),sep="_")
> t_ma
Hi all,
i am trying to use the 'spca' function of 'elasticnet' package. But i am
confused with the parameter 'para'.
Basically the parameter 'para' depends on the parameter 'sparse'. If
sparse="penalty", para is a vector of 1-norm penalty parameters. If
sparse="varnum", para deï¬nes the number o
If you have unicode strings, you may need to do even more because
there are often multiple ways of representing the same glyph. I made a
little demo at http://rpubs.com/hadley/unicode-normalisation, since
any unicode characters are likely to get mangled by email.
Hadley
On Fri, Jul 18, 2014 at 11
On Fri, Jul 18, 2014 at 11:17 AM, John McKown
wrote:
> Well, this was a shock to me. And I don't really see any documentation
> about it, but perhaps I just can't see it.
>
>>"abc" == "abc "
> [1] FALSE
>
> I guess that I thought of strings in R like I do is some other
> languages where the shorte
On 07/19/2014 07:17 PM, William Dunlap wrote:
Wrap all your calls to plot() with print(). E.g., change
plot(s, type="vectors", idx=1:12, main="")
to
print(plot(s, type="vectors", idx=1:12, main="")
Some plot methods require their output to be printed to display, some
don't. Some help f
Dear All,
wonder if someone could point me in the direction of calculating confidence
intervals for model parameters generated by nlxb() in the nlmrt package?
confint() as is gives the following message: no applicable method for 'vcov'
applied to an object of class "nlmrt". appreciate the input
Wrap all your calls to plot() with print(). E.g., change
plot(s, type="vectors", idx=1:12, main="")
to
print(plot(s, type="vectors", idx=1:12, main="")
Some plot methods require their output to be printed to display, some
don't. Some help files for plot methods mention this requirement,
so
On 07/19/2014 01:25 PM, Duncan Murdoch wrote:
On 19/07/2014, 5:41 AM, Ingo Wardinski wrote:
Hello,
I try to plot some results of an analysis to multiple individual
postscript files, like:
postscript("A1_zonflow.ps",onefile=F)
plot(s, type = "vectors", idx = 1:12,main="")
dev.off()
#
You could use tapply() and cut() in base R, as in
> tapply(d$z, INDEX=list(y=cut(d$y,breaks=seq(900,1300,by=100)),
> x=cut(d$x,breaks=seq(35,60,by=5))), FUN=mean)
x
y(35,40] (40,45] (45,50] (50,55] (55,60]
(900,1e+03] 1644.779 1643.957 NA
Hi Mark,
First you need to use cut() to bin the values. Here's an example:
# generate some fake data
temp <- data.frame(x=runif(20), y=runif(20), z=runif(20))
# bin x and y
temp$x <- cut(temp$x, seq(0, 1, by=.2))
temp$y <- cut(temp$y, seq(0, 1, by=.2))
>From there, there are all sorts of ways to
This is probably a basic question, but I haven't been able to Google
anything helpful after trying for days.
I have an R dataframe with x,y,z tuples, where z is a response to x and y
and can be modeled as a surface.
> head(temp)
x yz
1 36.55411 965.7779 1644.
On 19/07/2014, 5:41 AM, Ingo Wardinski wrote:
> Hello,
> I try to plot some results of an analysis to multiple individual
> postscript files, like:
>postscript("A1_zonflow.ps",onefile=F)
>plot(s, type = "vectors", idx = 1:12,main="")
>dev.off()
> #
>postscript("vectors_paired_zonfl
On Fri, 18 Jul 2014 10:15:35 AM Veronica Andreo wrote:
> Hi list
>
> I have a vector, which are remotely sensed chlorophyll values for a
certain
> pixel in 11 years, then i have a flag or label vector (t_max) that
consists
> of 0 and 1, which tells me where i have the annual peak (one per
year,
Hello,
I try to plot some results of an analysis to multiple individual
postscript files, like:
postscript("A1_zonflow.ps",onefile=F)
plot(s, type = "vectors", idx = 1:12,main="")
dev.off()
#
postscript("vectors_paired_zonflow.ps",onefile=F)
plot(s, type = "paired", idx = 1:12,plot.con
Dear list members
I appreciate if anyone share with or direct me to a source or R code for
forecasting ARDL(p,q) times series using Monte Carlo simulation.
Kind regards
I. Mohamed, CBE, UAEU
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