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I'm trying to perform the LSCV.density function (which replaced the CV.sm function in the prior versions) as part of bivariate kernal density estimation in the sparr package.

own <- readOGR(".", "caseControlOWIN2") myWin <- owin(poly=list( x = rev(own@polygons[[1]]@Polygons[[1]]@coords[-1,1]), y = rev(own@polygons[[1]]@Polygons[[1]]@coords[-1,2]))) plot(myWin) data.sp <- spTransform(data.sp, CRS("+proj=lonlat +datum=WGS84") + point(data.sp) points(data.sp) coordinates(data.sp) data.sp$finalid == "STY" which( data.sp$finalid == "STY") length(which( data.sp$finalid == "STY")) plot(myWin) points(data.sp[data.sp$finalid == "STY",]) points(data.sp[data.sp$finalid == "NEG",]) plot(myWin) plot(myWin, main = "cases") axis(1) axis(2) n1 <- length(which( data.sp$finalid == "STY")) n2 <- length(which( data.sp$finalid == "NEG")) LSCV.density(data, hlim=NULL, res=128, edge=TRUE, WIN=myWIN, quick=FALSE, comment=TRUE) Initialising... Error in LSCV.density(data, hlim = NULL, res = 128, edge = TRUE, WIN = myWIN, : object 'myWIN' not found

So shouldn't it recognize myWin from what I typed in earlier? what am I doing wrong here?

user2980671
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1 Answers1

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When R says something is 'not found' it usually refers to an object you've asked for not being present in the current workspace. In your case, you have defined myWin, but in calling the function, you've used myWIN...

This should be a good starting point, though I haven't run your code to see if there are any more errors yet.

Tilman Davies
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