I completely agree with Thierry. Take a look at this also: https://stat.ethz.ch/pipermail/r-sig-geo/2008-February/003176.html
The instructions on how to run RK with binary variables in R you can find in sec 4.3.3 (Fig. 4.15) of my lecture notes. Hengl, T., 2007. A Practical Guide to Geostatistical Mapping of Environmental Variables. EUR 22904 EN Scientific and Technical Research series, Office for Official Publications of the European Communities, Luxemburg, 143 pp. http://bookshop.europa.eu/uri?target=EUB:NOTICE:LBNA22904:EN:HTML Tom Hengl http://spatial-analyst.net -----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of ONKELINX, Thierry Sent: woensdag 2 april 2008 11:56 To: Vanessa Stelzenmuller (Cefas); r-sig-geo@stat.math.ethz.ch Subject: Re: [R-sig-Geo] question about regression kriging Dear Vanessa, What residuals did you use? The ones in the original scale or in the logit scale? Interpolate the residuals in the logit scale and add these to the model predictions in the logit scale. And the transform those values back to the original scale. This will prevent values outside the 0-1 range. Maybe you should have a loot at the geoRglm package. HTH, Thierry ---------------------------------------------------------------------------- ir. Thierry Onkelinx Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest Cel biometrie, methodologie en kwaliteitszorg / Section biometrics, methodology and quality assurance Gaverstraat 4 9500 Geraardsbergen Belgium tel. + 32 54/436 185 [EMAIL PROTECTED] www.inbo.be To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of. ~ Sir Ronald Aylmer Fisher The plural of anecdote is not data. ~ Roger Brinner The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data. ~ John Tukey -----Oorspronkelijk bericht----- Van: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Namens Vanessa Stelzenmuller (Cefas) Verzonden: woensdag 2 april 2008 11:32 Aan: r-sig-geo@stat.math.ethz.ch Onderwerp: [R-sig-Geo] question about regression kriging Hello, We work on the application of regression kriging to presence / absence data in the context of species distribution modelling. In R in a first step we fit the trend surfaces with logistic regression models. Then we fit a variogram to the regression residuals and interpolate the residuals with OK. Now we face the situation that when combining trend surfaces with residual surfaces for some locations our occurrence probability is <0 or >1. Thus taking into account the spatial structure of the data (residuals) has the potential to convert a predicted high occurrence probability into a low occurrence probability or vice versa. Are there some restriction for presence/ absence data for this approach? How to deal with these estimations (<0 and >1)? Many thanks Vanessa ________________________________ Dr. Vanessa Stelzenmüller Marine Scientist (GIS), CEFAS Pakefield Road, Lowestoft, NR33 0HT, UK Tel.: +44 (0)1502 527779 www.cefas.co.uk *********************************************************************************** This email and any attachments are intended for the =\...{{dropped:8}} _______________________________________________ R-sig-Geo mailing list R-sig-Geo@stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-sig-geo
