Message-ID: <70F05367-DAD4-46EE-9B9A-5119D235ACF2@comcast.net>
Date: 2009-11-30T15:48:36Z
From: David Winsemius
Subject: Joint density approximation?
In-Reply-To: <7dc3eb8d0911300630r46b16e55r54560b66e2b3c395@mail.gmail.com>
On Nov 30, 2009, at 9:30 AM, Trafim wrote:
> Unfortunately, it doesn't work.
> Can you, please, help me with it?
>
In order to support the notion of a 2 dimensional distribution, you
need a function that depends on ... 2 dimensions. All you have at the
moment are two different one-dimensional functions.
What is you goal in this effort?
--
David.
> Thanks a lot.
>
> On Mon, Nov 30, 2009 at 2:53 PM, Trafim <rdapamoga at gmail.com> wrote:
>
>> Seems that I found it - kde2d
>>
>>
>> On Mon, Nov 30, 2009 at 2:36 PM, Trafim <rdapamoga at gmail.com> wrote:
>>
>>> Hi everybody,
>>>
>>> I am looking for the possibility in R to estimate joint density,
>>> just for
>>> example:
>>>
>>> x <- seq(1,40,1)
>>> y <- 2*x+1+5*rnorm(length(x))
>>> y1 <- x^3+.5*rnorm(length(x))
>>>
>>> Is there a way to approximate the density function s.t. I will
>>> later be
>>> able to calculate f(Y=y, Y1=y1)
>>>
>>> Thanks a lot
>>>
>>>
>>
>
> [[alternative HTML version deleted]]
>
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David Winsemius, MD
Heritage Laboratories
West Hartford, CT