Roger, I think all I would like to know is if it is possible to apply a calibrated GWR model to a hold-out sample, and if so, what the most accurate way to do so is. I understand the pitfalls of GWR but would like to learn as much as I can before progressing to the next spatial methodology I learn in R.
On Fri, Aug 30, 2013 at 3:37 AM, Roger Bivand <roger.biv...@nhh.no> wrote: > Paul, Luis, > > I suspect that your speculations are completely wrong-headed. Please > provide a reproducible example with a built-in data set, so that there is > at least minimal clarity in what you are guessing. Note in addition that > GWR as a technique should not be used for anything other than exploration > of possible mis-specification in the underlying model with the given data, > as patterning in coefficients is induced by GWR for simulated covariates > with no pattern. > > Roger > > > On Fri, 30 Aug 2013, Luis Guerra wrote: > > 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<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<https://stat.ethz.ch/mailman/listinfo/r-sig-geo> >> >> > -- > Roger Bivand > Department of Economics, NHH Norwegian School of Economics, > Helleveien 30, N-5045 Bergen, Norway. > voice: +47 55 95 93 55; fax +47 55 95 95 43 > e-mail: roger.biv...@nhh.no > > -- Paul Bidanset (757) 412-9217 pbidan...@gmail.com [[alternative HTML version deleted]] _______________________________________________ R-sig-Geo mailing list R-sig-Geo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
