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</o:shapelayout></xml><![endif]--></head><body lang=EN-US link=blue vlink=purple><div class=WordSection1><p class=MsoNormal>I have what I think is a simple question for producing kerneloverlap indices in the adehabitat package but I am having trouble with a solution. The basic problem is to use kernel overlap indices to compare different home range techniques for a given animal.<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>I think the solution is in understanding how to create my own object of khrud that contains UD’s generated with different h parameters or home range methods so that I can quantify how the different home range methods compare. I have put together the following code from the samples using my own data, but the solution for my problem seems to be in creating my own khrud object containing UD’s generated using different methods that I can feed into the kerneloverlaphr function???? Maybe there is another solution?<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Can anyone help? I have provided a simple example to start.<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Thanks,<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Andy<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>#######################################################<o:p></o:p></p><p class=MsoNormal>library(adehabitat)<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>elk_tele_all <- read.table("ElkTelemetry_20100917_SPS_LE_660Feet_Final.txt", header= TRUE, sep = ",")<o:p></o:p></p><p class=MsoNormal>elk_tele_all<o:p></o:p></p><p class=MsoNormal>names(elk_tele_all)<o:p></o:p></p><p class=MsoNormal>elk_tele_test <- subset(elk_tele_all, ElkName == 'Delores' | ElkName == 'Gertrude' | ElkName == 'Clover' | ElkName == 'Eunice')<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>##Get the locations and animal names<o:p></o:p></p><p class=MsoNormal>loc <- elk_tele_test[, c("X_SPS", "Y_SPS")]<o:p></o:p></p><p class=MsoNormal>id <- elk_tele_test[, "ElkName"]<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>## Estimation of UD for the four animals<o:p></o:p></p><p class=MsoNormal>(ud <- kernelUD(loc, id, h = "href"))<o:p></o:p></p><p class=MsoNormal>image(ud) ## Note that the contours<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>## Example of estimation using LSCV<o:p></o:p></p><p class=MsoNormal>udbis <- kernelUD(loc, id, h = "LSCV")<o:p></o:p></p><p class=MsoNormal>image(udbis) ## Note that the contours<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>##This works to compare the four animals<o:p></o:p></p><p class=MsoNormal>kerneloverlap(loc, id,<o:p></o:p></p><p class=MsoNormal>grid=200, meth="VI", conditional=TRUE)<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>## Identical to<o:p></o:p></p><p class=MsoNormal>kud <- kernelUD(loc, id,<o:p></o:p></p><p class=MsoNormal>grid=200, same4all=TRUE)<o:p></o:p></p><p class=MsoNormal>kerneloverlaphr(kud, meth="VI", conditional=TRUE)<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>##But how do I compare the href and LSCV methods on a per animal basis?<o:p></o:p></p><p class=MsoNormal>##Once I can figure out this simple method, then I can work on more advanced applications of CVh, BBMM, HPI, etc<o:p></o:p></p><p class=MsoNormal>???????<o:p></o:p></p><p class=MsoNormal>#######################################################<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p></div></body></html>