On a Clustering Criterion for Dependent Observations
Statistics Theory
2013-11-19 v1 Probability
Statistics Theory
Abstract
A univariate clustering criterion for stationary processes satisfying a -mixing condition is proposed extending the work of \cite{KB2} to the dependent setup. The approach is characterized by an alternative sample criterion function based on truncated partial sums which renders the framework amenable to various interesting extensions for which limit results for partial sums are available. Techniques from empirical process theory for mixing sequences play a vital role in the arguments employed in the proofs of the limit theorems.
Cite
@article{arxiv.1311.3998,
title = {On a Clustering Criterion for Dependent Observations},
author = {Karthik Bharath},
journal= {arXiv preprint arXiv:1311.3998},
year = {2013}
}