> Thank you Luis. When calibrating the adaptive model, using adapt=t in the > bandwidth selection created the proportion you speak of, which then allowed > me to create a bandwidth matrix using gwr.adapt. However, this has not > worked for me with holdout samples. Have you had success in this regard? > Now I get what you mean. Let's show an example:
bw <- gwr.sel(var ~ var1, data=yourdata, adapt=TRUE) m <- gwr(var~var1, data=yourdata, adapt=bw, fit.points=newdata) So an adaptative bandwidth (bw) is calculated based on"yourdata", while you are fitting "newdata" later on using that previously found bw. I had not thought about it previously. Let's see whether someone else can help you (us). > I do not know the intended influence of these "fit.points". I would think > that new localized regressions are not calculated, as we're testing the > model and previous data points' ability to predict for these new ones, but > I could be wrong. My current method, however, is producing much poorer > results with the holdouts, which I am fairly sure is related to my > inability to incorporate the new points necessary bandwidths. > Coming back to the previously created example, imagine that "newdata" is a single point that you want to fit. Imagine now that "yourdata" is a sample with 1000 cases. Then you are getting 1000 models with 1000 different intercepts and 1000 different beta values to adjust var1, rigth? Which of all these parameters do you use for fitting "newdata"? And something else, what would happen with "newdata" if it is enough far away from "yourdata" and we would be using a fixed bandwidth? > On Aug 29, 2013 8:56 PM, "Luis Guerra" <luispelay...@gmail.com> wrote: > >> Dear Paul, >> >> I am dealing with this kind of problems right now, and if I am not wrong, >> when you want to apply an adaptative bandwidth, you should introduce a >> value for the "adapt" parameter instead of for the "bandwidth" parameter. >> This value will be between 0 and 1 and indicates the proportion of cases >> around your regression point that should be included to estimate each local >> model. So depending on the amount of points around each case, the model >> will use a different bandwidth for each point to be fitted. >> >> Related to your question, do you know what is the influence of the data >> introduced in the "data" parameter to the data to be fitted (introduced in >> the "fit.points" parameter)? I mean, you have to obtain new local models >> (one for each point to be fitted), so I do not understand whether the >> "data" parameter is used somehow... >> >> Best regards, >> >> Luis >> >> >> On Fri, Aug 30, 2013 at 1:26 AM, Paul Bidanset <pbidan...@gmail.com>wrote: >> >>> Hi Folks, >>> >>> I was curious if anyone has had experience applying an SPGWR model with >>> an >>> adaptive bandwidth matrix to a holdout or validation sample. I am using >>> the >>> "fit.points" command, which does not seem to allow for a new bandwidth >>> calibrated around the holdout samples XY coordinates. Any direction would >>> be greatly appreciated. I am also open to other viable methods. >>> >>> Cheers, >>> >>> Paul >>> >>> [[alternative HTML version deleted]] >>> >>> _______________________________________________ >>> R-sig-Geo mailing list >>> R-sig-Geo@r-project.org >>> https://stat.ethz.ch/mailman/listinfo/r-sig-geo >>> >> >> [[alternative HTML version deleted]] _______________________________________________ R-sig-Geo mailing list R-sig-Geo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
