Contour of data points using Kernel Density Estimate.

Source: R/kde.R

This function calculates contour points and area from list of data.frames with data in 2d. Basically this is a wrapper of ks::kde.

kde_from_list(
  dflist,
  alpha,
  h_band = NULL,
  position = 1:2,
  grid_size = rep(1000, 2)
)

Arguments

dflist

list of data frames
alpha

contour level, an scalar from the sequence .01 to .99 by step size .01. For example, a value of .95 gives a contour level associated with the cumulative prob of 95% (and 95% confidence interval)
h_band

optional argument for the bandwidth of the kde object. If NULL, the optimal band would be selected through the ks::kde function. Default is NULL.
position

Columns position of x/y pair. Default is 1:2
grid_size

size of the grid which is going to be used for the evaluation of kde object. Can be reduced to speed-up computation.

Value

contour List of contour(s) at the specified level

Details

This function (renamed as kde_from_tclist) is shared with TCpredictionbands on github: TCpredictionbands.