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# Flux for sparse data

I need to learn how to compute the flux for sparse data.

I looked at the volumetric GPM data for precipitation and it does not look like a continuous function, rather it is sparse partitioned and distanced spread of regions of moisture.

So my previous work to compute the Laplacian might or might not apply.

I was wondering how one goes about mathematically computing the flux of sparse data.

Dara

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1.

AKA Gaussian process regression and a form of geo-spatial interpolation

Comment Source:Kriging? <http://en.wikipedia.org/wiki/Kriging> AKA Gaussian process regression and a form of geo-spatial interpolation
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2.

thanx paul, I study this

Comment Source:thanx paul, I study this
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3.

Paul check out the NonlinearModelFit [ ] in Mathematica I think it is using the Gaussian process.

Comment Source:Paul check out the NonlinearModelFit [ ] in Mathematica I think it is using the Gaussian process.
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4.

Dara, I am using these options for NonLinearModelFit :

Method -> "NMinimize"

Method -> "Differential Evolution"

Comment Source:Dara, I am using these options for NonLinearModelFit : Method -> "NMinimize" Method -> "Differential Evolution"
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5.

You are a genius Paul.

Paul Mathematica's Differential Evolution is not parallelized, I want to write a version in C that is parallelized in GPU servers.

Dara

Comment Source:You are a genius Paul. Paul Mathematica's Differential Evolution is not parallelized, I want to write a version in C that is parallelized in GPU servers. Dara
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6.

Dara, I still do not know if the Eureqa tool I occasionally use incorporates Differential Evolution, but it certainly does use all 8 of the CPU's when it is running.

Paul

Comment Source:Dara, I still do not know if the Eureqa tool I occasionally use incorporates Differential Evolution, but it certainly does use all 8 of the CPU's when it is running. Paul