UPMASK: Unsupervised Photometric Membership Assignment in Stellar Clusters

An implementation of the UPMASK method for performing membership assignment in stellar clusters in R. It is prepared to use photometry and spatial positions, but it can take into account other types of data. The method is able to take into account arbitrary error models, and it is unsupervised, data-driven, physical-model-free and relies on as few assumptions as possible. The approach followed for membership assessment is based on an iterative process, dimensionality reduction, a clustering algorithm and a kernel density estimation.

Package details

AuthorAlberto Krone-Martins [aut, cre], Andre Moitinho [aut], Eduardo Bezerra [ctb], Leonardo Lima [ctb], Tristan Cantat-Gaudin [ctb]
MaintainerAlberto Krone-Martins <algol@sim.ul.pt>
LicenseGPL (>= 3)
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the UPMASK package in your browser

Any scripts or data that you put into this service are public.

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