[R] KDE on a large dataset (15 million points)
maurizio.gibin at jrc.ec.europa.eu
Thu Apr 9 13:11:14 CEST 2015
I am having some troubles in calculating a kde surface from a datatable.
The code is efficient in my opionion, but I have a problem on the output.
After some modelling that is not relevant for the purpose of my question
I obtain a data.table of around 15 million records (for half a year, I
forecast around 50 millions for the entire year).
The data.table is pretty simple, just lat and lon.
Let's forget for a second the problems related to projection, and focus
on the K(ernel)D(ensity)E(stimation). Do you have any suggestion on a
library that could be able to cope with so many points?
I know I could calculate the density in different ways and through
different platforms, however, I would like to stick to R as it is
commonly diffused in research.
I also know that probably subsetting the dataset is a wise choice...
*MAURIZIO GIBIN **
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