t;
> --David.
>
> > The reason I don’t want to use sampling (with
> replacement, I can sample more data than I have without
> replacement), as this will generate lots of duplicate data
> points, if I want to generated bigger dataset yet my raw
> data do not have a big samp
will
generate lots of duplicate data points, if I want to generated
bigger dataset yet my raw data do not have a big sample size. The
scatter plot of the sampled data doesn’t look good this way.
Heyi
--- On Fri, 3/23/12, David Winsemius wrote:
From: David Winsemius
Subject: Re: [R
not have
a big sample size. The scatter plot of the sampled data doesn’t look good this
way.
Heyi
--- On Fri, 3/23/12, David Winsemius wrote:
> From: David Winsemius
> Subject: Re: [R] Nonparametric bivariate distribution estimation and sampling
> To: "heyi xiao"
>
particular
suggestions/comments, you are more than welcome. Thanks!
Heyi
--- On Fri, 3/23/12, Sarah Goslee wrote:
From: Sarah Goslee
Subject: Re: [R] Nonparametric bivariate distribution estimation
and sampling
To: "heyi xiao"
Cc: r-help@r-project.org
Date: Friday, March 23
not clear enough. If you have any particular suggestions/comments, you are
more than welcome. Thanks!
Heyi
--- On Fri, 3/23/12, Sarah Goslee wrote:
> From: Sarah Goslee
> Subject: Re: [R] Nonparametric bivariate distribution estimation and sampling
> To: "heyi xiao"
> Cc
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, yo
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 t
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