R help - Mar 2012 - Nonparametric bivariate distribution estimation and sampling

Dear all,
I have a bivariate dataset from a preliminary study. I want to do two things:
(1) estimate the probability density of this bivariate distribution using some
nonparametric method (kernel, spline etc); (2) sample a big dataset from this
bivariate distribution for a simulation study.
Is there any good method or package I can use in R for my work? I don?t want
parametric models like bivariate normal distribution etc, as I would like to
accurate model my data. I don?t want to use the bootstrapping approach, i.e.
sampling with replacement, as this will generate lots of duplicate data points.
Any thoughts or input will be highly appreciated!
Heyi

R can do all of that and more.

But you'll need to put some work in reading about how to use R, about
the statistical methods involved, and about how to use them to best
effect. You might want, for instance, generalized additive models. Or
not. If your question isn't more fully-formed than this, your best bet
is almost certainly to talk to a local statistician, spend some time
working with R, and then come back to the list with specific
questions.

Sarah

On Fri, Mar 23, 2012 at 12:17 PM, heyi xiao <xiaoheyiyh at yahoo.com>
wrote:
> Dear all,
> I have a bivariate dataset from a preliminary study. I want to do two
things: (1) estimate the probability density of this bivariate distribution
using some nonparametric method (kernel, spline etc); (2) sample a big dataset
from this bivariate distribution for a simulation study.
> Is there any good method or package I can use in R for my work? I don?t
want parametric models like bivariate normal distribution etc, as I would like
to accurate model my data. I don?t want to use the bootstrapping approach, i.e.
sampling with replacement, as this will generate lots of duplicate data points.
Any thoughts or input will be highly appreciated!
> Heyi
>
>
-- 
Sarah Goslee
http://www.functionaldiversity.org