Use a kernel density estimator to model the density of samples along a 2-dimensional grid

`kde2d(x, y, n.bins = 100, x.bin = NA, y.bin = NA)`

- x
n by m matrix where n is the number of observations and m is >= 1

- y
n by j matrix where n is the number of observations and j is >= 1

- n.bins
number bins over which to calculate intervals. Used to calculate x.bin if not provided.

- x.bin
vector of bin edges over which to bin.

- y.bin
vector of bin edges over which to bin.

A list with a matrix of density, x.bin and y.bin

Other gridding:
`bin2d()`

,
`quantile2d()`

Other plot help:
`AD2BP_trans()`

,
`BP2AD_trans()`

,
`axisLabel()`

,
`bin2d()`

,
`geoChronRPlotTheme()`

,
`getLegend()`

,
`getPlotRanges()`

,
`meltDistributionTable()`

,
`modeSelektor()`

,
`periodAnnotate()`

,
`quantile2d()`

,
`reverselog10_trans()`