analyse_randomKde2d_AutoCalibrated: Perform analysis of random 2d distributions (auto calibrated)

In UPMASK: Unsupervised Photometric Membership Assignment in Stellar Clusters

Description

The experimental code analyse_randomKde2d_AutoCalibrated computes statistics from uniformly randomly created 2D fields based on kernel density estimations (using create_randomKde2d). It runs for as many interations as necessary for the statistical measuremnt stabilize (but it will abort after maxIter iterations is reached).

Usage

analyse_randomKde2d_AutoCalibrated(nstars, maxX, maxY, nKde=50, maxIter=40, 
                                          showStats=FALSE, returnStats=TRUE)

Arguments

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
maxIter	an integer with the maximum number of iterations
showStats	a boolean indicating if the user wants to see statistics
returnStats	a boolean indicating if the user wants statistics to be returned

Value

A data frame with the mean and sd fields containing the results of the random field analysis.

Author(s)

Alberto Krone-Martins, Andre Moitinho

Examples

# Runs the analysis on random fields
toyRes <- analyse_randomKde2d_AutoCalibrated(100, 100, 100, 100, showStats=TRUE)

# Clean the environment
rm(toyRes)
 

UPMASK documentation built on May 2, 2019, 2:39 p.m.