SPGWR Application to Holdout Sample
On Tue, 29 Apr 2014, Paul Bidanset wrote:
Hello, I was just curious - am I safe in assuming that when applying holdout data (new data points not included in model calibration) to GWR models in the SPGWR package (as below), each new point is applied to the local regression model in closest geographic proximity?
No, you are not safe. The #fit.points models fitted are fitted at - hence the name - the fit points, using the kernel and bandwidths specified. In this case, the data in the data= argument are geographically weighted in these #fit.points models, but never fitted themselves. Please do not use HTML, and do provide an example in which georgiaNewData is made explicit (is it a subset of gSRDF?). Hope this clarifies, Roger
* PredictionsOfNewData <- gwr(PctBach ~ TotPop90 + PctRural + PctEld +
*>>>* PctFB *>>>* + PctPov + PctBlack, data=gSRDF, adapt=TRUE, gweight=gwr.Gauss, method = *>>>* "aic", bandwidth=bw1, *>>>* predictions=TRUE, fit.points=georgiaNewData) *>>>* PredictionsOfNewData* Thank you in advance for your assistance. Best, Paul [[alternative HTML version deleted]]
_______________________________________________ R-sig-Geo mailing list R-sig-Geo at r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
Roger Bivand Department of Economics, Norwegian School of Economics, Helleveien 30, N-5045 Bergen, Norway. voice: +47 55 95 93 55; fax +47 55 95 91 00 e-mail: Roger.Bivand at nhh.no