I haven't tested it but the first thing I'd look at is scale_fill_gradient.
HTH
Ulrik
Jim Lemon schrieb am Do., 11. Mai 2017, 07:22:
> Hi Kristi,
> It can be done, but it is messy:
>
> pl = data.frame(Time = 0:10, menle = rnorm(11))
> pl$menlelb = pl$menle -1
> pl$menleub = pl$menle +1
> rg<
Hi Kristi,
It can be done, but it is messy:
pl = data.frame(Time = 0:10, menle = rnorm(11))
pl$menlelb = pl$menle -1
pl$menleub = pl$menle +1
rg<-0.95
blue<-1
plot(pl$Time,pl$menlelb,ylim=range(c(pl$menlelb,pl$menleub)),type="l",
lwd=7,col=rgb(rg,rg,blue))
lines(pl$Time,pl$menlelb,lwd=7,col=rgb(r
I haven't gone through your code carefully, but I believe this can be done
in a tiny fraction of the time you are taking by eschewing loops. See
?expand.grid to get started. In general,nested loops should be avoided if
possible.
I also suggest you spend some time with a good R tutorial to learn h
> On May 10, 2017, at 11:20 AM, Santiago Burone
> wrote:
>
> Hello,
>
> I'm new at R and I would like to use it in order to solve a system of non
> linear equations. I have the code that works but im not able to save the
> results.
>
>
>
> My system has three equations and i would like
Hello,
I'm new at R and I would like to use it in order to solve a system of non
linear equations. I have the code that works but im not able to save the
results.
My system has three equations and i would like to solve this using three nested
loops, becouse i need solutions for all the va
Hi R Users,
I was trying to create a figure with geom_ribbon. There is a function "fill",
but I want to make the shaded area with a gradient (increasing dark color
towards a central line, inserted of having a color). Is there any possibility?
In the given example, I want the colour with "blue"
> On May 10, 2017, at 11:02 AM, Czarek Kowalski wrote:
>
> Previously I had used another language to make calculations based on
> theory. I have calculated using R and I have received another results.
> My theoretical calculation does not take into account the full
> covariance matrix (only 6 el
It's not obvious to me that that marginal distribution of one component of a
multivariate truncated t is the corresponding univariate truncated t.
In fact, I would expect it to differ because of tail-dependence effects, e.g.
> r <- rtmvt(1e5, c(30,0), diag(2), lower=c(29,-Inf), upper=c(31, +Inf)
Previously I had used another language to make calculations based on
theory. I have calculated using R and I have received another results.
My theoretical calculation does not take into account the full
covariance matrix (only 6 elements from diagonal). Code based on
theory:
df = 4; #degrees of
I have a fair bit of experience with both nls and rating curves. This is
not a nls() problem, this is a model problem. The power law rating curve
favored by hydrologists would not apply to your data as it's based on
the idea that a log-log plot of discharge vs. stage, or state+a in your
case is
Thanks for confirming that I wasn't being stupid :-}
When using default=pathlong I get the _correct_ starting directory...
(M:\test\Averyveryveryveryverylongfoldername\Averyveryveryveryverylongfoldername\Averyveryveryveryverylongfoldername)
... both in the environment I indicated originally (Wi
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