Sorry, maybe I confused everybody with what I want. I have time process X_k, and corresponding returns process R_k I am interesting in f(r|x), which I can find knowing f(r,x) and f(x). I know the latter I need the first.
How can I apploximate this f(r,x) in the such way that later I can find f(X=x,R=r) not for the values from X_k, R_k timeseries, but for some predefined grid values. I looked at the kde2d but it allows only the square matrix + I think from this matrix I can only get values f(x,r) in the pairs from (X_k, R_k) but not the other I want. Thanks a lot for any help and suggestions. On Mon, Nov 30, 2009 at 5:09 PM, Trafim <rdapam...@gmail.com> wrote: > Also what if the grid matrix is not squared? How can I then find this > kernel density matrix/ > > Thanks a lot. > > > On Mon, Nov 30, 2009 at 4:56 PM, Trafim <rdapam...@gmail.com> wrote: > >> You are right. >> I brought this example just to see how to use its with two time series. In >> reality I have price process and returns, and I need conditional density. >> >> Will highly appreciate your help. >> >> I found function kde2d but cannot understand how to call for the values of >> the matrix. >> >> >> >> On Mon, Nov 30, 2009 at 4:48 PM, David Winsemius >> <dwinsem...@comcast.net>wrote: >> >>> >>> 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 <rdapam...@gmail.com> wrote: >>>> >>>> Seems that I found it - kde2d >>>>> >>>>> >>>>> On Mon, Nov 30, 2009 at 2:36 PM, Trafim <rdapam...@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]] >>>> >>>> >>>> ______________________________________________ >>>> R-help@r-project.org mailing list >>>> https://stat.ethz.ch/mailman/listinfo/r-help >>>> PLEASE do read the posting guide >>>> http://www.R-project.org/posting-guide.html >>>> and provide commented, minimal, self-contained, reproducible code. >>>> >>> >>> David Winsemius, MD >>> Heritage Laboratories >>> West Hartford, CT >>> >>> >> > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
