Hi - Thanks for the tips on automap and intamap. I've compared kriging and
idw and see very little benefit from kriging and kriging takes about 3x as
long to run (15min vs 5 min or so) so I've decided to stick with IDW. I
have a large domain with over 5million points so are there any methods
implemented that are not brute force?

Dominik Schneider
o 303.735.6296 | c 518.956.3978



On Tue, Aug 13, 2013 at 7:38 AM, Jon Olav Skoien <
jon.skoien@jrc.ec.europa.eu> wrote:

> Dominik,
>
> The brute force approach shown in the link from Tom has in the mean time
> been implemented in the intamap package. See the example for the function
> "estimateParameters".
>
> Cheers,
> Jon
>
>
> On 13-Aug-13 1:54, Thomas Adams wrote:
>
>> Dominik,
>>
>> Look here:
>> http://r-sig-geo.2731867.n2.**nabble.com/GSTAT-Optimize-**
>> power-value-for-IDW-td2765918.**html<http://r-sig-geo.2731867.n2.nabble.com/GSTAT-Optimize-power-value-for-IDW-td2765918.html>
>>
>> Tom
>>
>>
>> On Mon, Aug 12, 2013 at 5:17 PM, Dominik Schneider <
>> Dominik.Schneider@colorado.edu**> wrote:
>>
>>  Hi,
>>> I'd like to optimize the IDW power, similar to what ArcGIS does. I found
>>> this old thread
>>> http://www.mail-archive.com/r-**sig-geo@stat.math.ethz.ch/**
>>> msg04011.html<http://www.mail-archive.com/r-sig-geo@stat.math.ethz.ch/msg04011.html>but
>>> was hoping someone could help adapt the solution. I am using
>>>
>>>
>>> idw(residuals(mdl.stepaic[[j]]**)~1,locations=swe.nozeros[swe.**
>>> nozeros$mth==mth
>>> & swe.nozeros$yr==yr,],newdata=**swe.grid)
>>>
>>> where mdl.stepaic[[j]] is a list of 39 regression equations. swe.nozeros
>>> is
>>> a spatialpointsdataframe of observations. swe.grid is a grid where I want
>>> new values predicted. I currently run this idw command through a loop of
>>> j
>>> with no problems but I'd like to optimize both within each equation
>>> represented by j and for the whole data set (so across the 39 timesteps).
>>>
>>> Below is what I'm starting with but I don't really understand how to get
>>> it
>>> working. I appreciate your help.
>>>
>>> f= function(idp,formula,**locations,newdata,...) {
>>>
>>> sum(idw(formula,locations,**newdata),set=list(debug=0,idp=**
>>> idp),...)$residuals**2
>>> }
>>>
>>> optimize(f,interval=seq(1.4,1.**7,by=0.1),formula=residuals(**
>>> mdl.stepaic[[j]])~1,locations=**swe.nozeros[swe.nozeros$mth==**mth
>>> & swe.nozeros$yr==yr,],newdata=**swe.grid)
>>>
>>>          [[alternative HTML version deleted]]
>>>
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>>>
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>>
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>>
>
>
> --
> Jon Olav Skøien
> Joint Research Centre - European Commission
> Institute for Environment and Sustainability (IES)
> Land Resource Management Unit
>
> Via Fermi 2749, TP 440,  I-21027 Ispra (VA), ITALY
>
> jon.skoien@jrc.ec.europa.eu
> Tel:  +39 0332 789206
>
> Disclaimer: Views expressed in this email are those of the individual and
> do not necessarily represent official views of the European Commission.
>
>
>

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