create_randomKde2d: Compute the density based distance quantity using a 2D Kernel...
In UPMASK: Unsupervised Photometric Membership Assignment in Stellar Clusters

Description Usage Arguments Value Author(s) References Examples

create_randomKde2d will compute the 2D Kernel Density Estimation for a random sampling of the requested number of points and will return the quantiy (max(d)-mean(d))/sd(d), if the option returnDistance is set to TRUE.

1 2	create_randomKde2d(nstars, maxX, maxY, nKde=50, printPlots=FALSE, showStats=FALSE, returnDistance=FALSE)

`nstars`	an integer with the number of stars to consider
`maxX`	the length of the field in X
`maxY`	the length of the field in Y
`nKde`	the number of samplings of the kernel in each direction
`printPlots`	a boolean indicating if the user wants to see plots
`showStats`	a boolean indicating if the user wants to see statistics
`returnDistance`	a boolean indicating if the user wants statistics to be returned

A double representing the density based distance quantity.

Alberto Krone-Martins, Andre Moitinho

Krone-Martins, A. & Moitinho, A., A&A, v.561, p.A57, 2014

# Compute the density based distance quantity with random fields
distVar <- create_randomKde2d(100, 10, 10, showStats=FALSE, 
                              printPlots=FALSE, returnDistance=TRUE)

# Clean the environment
rm(distVar)