I have two columns of data, one is a subset of the other. All the data lie
beteen 0 and 1 inclusive. I want to fit both densities on the same graph. I
would also like the ability to extract the fitted values of both smoothed
density (using the best method of course).
For example, if
h = c( runif(1
Pradeep Raje gmail.com> writes:
>
> Thanks David for your response.I had done that.
But not shared it.
> Problem is not with the
> computations, but in the interpretation.
> Assume that x ordinates are 'time' [1:3472], and y are associated parameter
> values.
> Now density gives me 512/1024/2
Thanks David for your response.I had done that. Problem is not with the
computations, but in the interpretation.
Assume that x ordinates are 'time' [1:3472], and y are associated parameter
values.
Now density gives me 512/1024/2048 x-ordinates, of which some (7 to be
precise) are negative. What do
I am afraid your notion of a "concrete idea" is less concrete than
what I would need to understand what you are requesting. Your first
lines of example code should be:
library()
density(x, )
... since stats::density() by default would return 512 y estimates,
even if the length of x we
Dear all:Request your indulgence. The econophysics gurus do this stuff all
the time: all their PDFs are smooth, with neat log x axis.
1. The kernel density estimate (KDE) function returns the empirical
probability density at 2^n points (min: 512). The big question is how do I
scale back the x-value
Dear List,
I am trying to estimate a 3 dimensional density through the DPpackage.
For example
# model
sigma <- matrix(c(0.1,0.05,0.05,0.05,0.1,0.05,0.05,0.05,0.1), ncol=3)
rnormm<- rmvnorm(n=100, mean=c(5,100,150), sigma=sigma)
sigma2 <- matrix(c(10,0.05,0.05,0.05,10,0.05,0.05,0.05,10), ncol=3)
) 408-8111
> -Original Message-
> From: [EMAIL PROTECTED]
> [mailto:[EMAIL PROTECTED] On Behalf Of Gunther Jansen
> Sent: Wednesday, April 23, 2008 4:59 AM
> To: r-help@r-project.org
> Subject: [R] Density estimation
>
> Hi,
>
> I am analysing a datase
Hi,
I am analysing a dataset containing genetic distances within and between
species. I want to show a overlap of the distributions of the intra- and
interspecific values; on a second graph I use a cut-off value to determine
these boundaries. As the dataset contains >30 000 values, I would like
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