Dear All, I am researching financial market microstructure and have approx 4 x 10^7 multivariate 2D data samples which I have counted into a 250 x 390 bin matrix (frequency counted 2D histogram) in order to more efficiently manage the volume of data. I now wish to construct a smooth kernel density estimate (Gaussian kernel function) using this binned data. Does anyone in the R community know of an R function (or S-plus or Mathematica or Matlab or C++ or even Fortran) to do this. (Note that bkde2D, ash2 etc will not work with binned data input and using 4 x 10^7 raw samples on a 0(n^2) algorithm is probably not feasible) Thanks in advance. Regards, James McCulloch Post-Doc Fellow University of Technology Sydney
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