rhrKDE: Kernel Density Estimation (KDE)
In jmsigner/rhr: Reproducible Home Ranges with R

Description Usage Arguments Details Value See Also

Function to estimate home ranges with kernel density estimation.

1
2
3

rhrKDE(xy, h = rhrHref(xy)$h, levels = 95,
  trast = rhrRasterFromExt(rhrExtFromPoints(xy, extendRange = 0.2), nrow =
  100, res = NULL))

`xy`	Instance of `data.frame`, `SpatialPoints`, `SpatialPointsDataFrame` or `RhrMappedData`. If `xy` is is a `data.frame`, then the first two columns are assumed to be the `x` and `y` coordinates of the relocations.
`h`	Numeric `vector` with the bandwidth of the kernel. A scalar value will be applied to both dimensions.
`levels`	Numeric `vector` indicating percentages at which the home-range estimates should be evaluated.
`trast`	Instance of `RasterLayer` that serves as a template for the resulting grid of the estimation.

Kernels densities are estimated with KernSmooth::bkde2d. This is a binned approximation of 2D kernel density estimates (see ?KernSmooth::bkde2d for more details.)

Object of class RhrKDE

KernSmooth::bkde2d, rhr::rhrHref, rhr::rhrHlscv, rhr::rhrHpi

jmsigner/rhr documentation built on June 26, 2020, 8:59 a.m.