Asymptotics of k-mean clustering under non-i.i.d. sampling

Regis J. Serinko; Gutti Jogesh Babu

doi:10.1016/0167-7152(94)00148-2

Asymptotics of k-mean clustering under non-i.i.d. sampling

Regis J. Serinko, Gutti Jogesh Babu

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Abstract

The asymptotic theory of k-mean clustering is extended to stationary mixing processes, both σ-mixing and strong-mixing. In addition, a consistency result is obtained for non-identically distributed independent observations.

Original language	English (US)
Pages (from-to)	57-66
Number of pages	10
Journal	Statistics and Probability Letters
Volume	24
Issue number	1
DOIs	https://doi.org/10.1016/0167-7152(94)00148-2
State	Published - Jul 1995

All Science Journal Classification (ASJC) codes

Statistics and Probability
Statistics, Probability and Uncertainty

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10.1016/0167-7152(94)00148-2

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title = "Asymptotics of k-mean clustering under non-i.i.d. sampling",

abstract = "The asymptotic theory of k-mean clustering is extended to stationary mixing processes, both σ-mixing and strong-mixing. In addition, a consistency result is obtained for non-identically distributed independent observations.",

author = "Serinko, {Regis J.} and Babu, {Gutti Jogesh}",

year = "1995",

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AU - Serinko, Regis J.

AU - Babu, Gutti Jogesh

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N2 - The asymptotic theory of k-mean clustering is extended to stationary mixing processes, both σ-mixing and strong-mixing. In addition, a consistency result is obtained for non-identically distributed independent observations.

AB - The asymptotic theory of k-mean clustering is extended to stationary mixing processes, both σ-mixing and strong-mixing. In addition, a consistency result is obtained for non-identically distributed independent observations.

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JO - Statistics and Probability Letters

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Asymptotics of k-mean clustering under non-i.i.d. sampling

Abstract

All Science Journal Classification (ASJC) codes

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