contour: Contours functions In ks: Kernel Smoothing

Description

Contour levels and sizes.

Usage

 ```1 2 3 4 5 6 7``` ```contourLevels(x, ...) ## S3 method for class 'kde' contourLevels(x, prob, cont, nlevels=5, approx=TRUE, ...) ## S3 method for class 'kda' contourLevels(x, prob, cont, nlevels=5, approx=TRUE, ...) contourSizes(x, abs.cont, cont=c(25,50,75), approx=TRUE) ```

Arguments

 `x` an object of class `kde` or `kda` `prob` vector of probabilities corresponding to highest density regions `cont` vector of percentages which correspond to the complement of `prob` `abs.cont` vector of absolute contour levels `nlevels` number of pretty contour levels `approx` flag to compute approximate contour levels. Default is TRUE. `...` other parameters

Details

–For `contourLevels`, the most straightforward is to specify `prob`. Heights of the corresponding highest density region with probability `prob` are computed. The `cont` parameter here is consistent with `cont` parameter from `plot.kde` and `plot.kda` i.e. `cont=(1-prob)*100`%. If both `prob` and `cont` are missing then a pretty set of `nlevels` contours are computed.

–For `contourSizes`, the approximate Lebesgue measures are approximated by Riemann sums. These are rough approximations and depend highly on the estimation grid, and so should be interpreted carefully.

If `approx=FALSE`, then the exact KDE is computed. Otherwise it is interpolated from an existing KDE grid. This can dramatically reduce computation time for large data sets.

Value

–For `contourLevels`, for `kde` objects, returns vector of heights. For `kda` objects, returns a list of vectors, one for each training group.

–For `contourSizes`, an approximation of the Lebesgue measure of level set, i.e. length (d=1), area (d=2), volume (d=3), hyper-volume (d>4).

`contour`, `contourLines`
 ```1 2 3 4 5 6``` ```set.seed(8192) x <- rmvnorm.mixt(n=1000, mus=c(0,0), Sigmas=diag(2), props=1) fhat <- kde(x=x, binned=TRUE) contourLevels(fhat, cont=c(75, 50, 25)) contourSizes(fhat, cont=25, approx=TRUE) ## compare to approx circle of radius=0.75 with area=1.77 ```