Campus Units

Statistics

Document Type

Article

Publication Version

Submitted Manuscript

Publication Date

2019

Journal or Book Title

arXiv

Abstract

The K-means algorithm is extended to allow for partitioning of skewed groups. Our algorithm is called TiK-Means and contributes a K-means type algorithm that assigns observations to groups while estimating their skewness-transformation parameters. The resulting groups and transformation reveal general-structured clusters that can be explained by inverting the estimated transformation. Further, a modification of the jump statistic chooses the number of groups. Our algorithm is evaluated on simulated and real-life datasets and then applied to a long-standing astronomical dispute regarding the distinct kinds of gamma ray bursts.

Comments

This is a pre-print of the article Berry, Nicholas S., and Ranjan Maitra. "TiK-means: K -means clustering for skewed groups." arXiv preprint arXiv:1904.09609 (2019). Posted with permission.

Copyright Owner

The Authors

Language

en

File Format

application/pdf

Published Version

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