Hello, I have a n*2 matrix, called "plan", which contains n observations from 2 variates. I want a kernel density estimate of the joint distribution of these 2 variates. I try : density(plan). Unfortunately, R thinks there is 2n observations (if n=10, 20 observations), where there is only n. How to to make a multivariate kernel density estimate ? Thank you very much. _________________________________________________________________ météo et bien plus encore ! [[alternative HTML version deleted]]
There's a nice package ('ks') which even allows you to specify a
matrix of
bandwidths (not only one bandwidth for each coordinate direction).
Hope this helps,
Emili
Missatge citat per Bruce Willy <croero at hotmail.com>:
>
> Hello,
>
> I have a n*2 matrix, called "plan", which contains n observations
from 2
> variates.
>
> I want a kernel density estimate of the joint distribution of these 2
> variates.
> I try : density(plan). Unfortunately, R thinks there is 2n observations (if
> n=10, 20 observations), where there is only n.
>
> How to to make a multivariate kernel density estimate ?
>
> Thank you very much.
> _________________________________________________________________
>
> m?t?o et bien plus encore !
>
> [[alternative HTML version deleted]]
>
>
Try bkde2D {KernSmooth} or kde2d {MASS}.
Bruce Willy wrote:> Hello,
>
> I have a n*2 matrix, called "plan", which contains n observations
from 2 variates.
>
> I want a kernel density estimate of the joint distribution of these 2
variates.
> I try : density(plan). Unfortunately, R thinks there is 2n observations (if
n=10, 20 observations), where there is only n.
>
> How to to make a multivariate kernel density estimate ?
>
> Thank you very much.
> _________________________________________________________________
>
> m?t?o et bien plus encore !
>
> [[alternative HTML version deleted]]
>
>
>
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>
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