kernels.RdKernels convert distance/ duration vectors to single numbers, with a certain weight for certain distances. In general, at 0 distance, these return a value of 1, and the value decreases as the distance increases, reaching 0 at the limit of the support.
kernel_gaussian(d, r = 100, reduce_fun = sum) kernel_parabola(d, r = 100, reduce_fun = sum) kernel_uniform(d, r = 100, reduce_fun = sum)
| d | The vector of distances/ durations. |
|---|---|
| r | The radius of interest for the kernel to aggregate data. |
| reduce_fun | The reduce function used to aggregate data. |
numeric, function (usually sum) of kernel-weighted distances or durations
Gaussian kernel is a truncated gaussian, where r = 4*sigma (i.e., std. dev = r/4).The density which is truncated away is 1 - erf(2 sqrt(2)), which is approximately 0.0000633. Parabola kernel is parabolic, decreasing with distance within radius r, and returns 0 elsewhere. It is a scaled Epanechnikov kernel. Uniform kernel returns 1 within radius r, 0 elsewhere.