Hello everyone,
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...
Thanks.




--

*MAURIZIO GIBIN **
*Scientific/Technical Project Officer

*
**European Commission**
*Joint Research Centre

Institute for the Protection and Security of the Citizen (IPSC)

Maritime Affairs Unit*
*TP05A

Via Enrico Fermi 2749*
*I-21027 Ispra (VA)*
*+39 0332 786770*
maurizio.gi...@jrc.ec.europa.eu*
***


**<mailto:maurizio.gi...@jrc.ec.europa.eu> *

______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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.

Reply via email to