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

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  • Serinko, Regis J.
  • Babu, Gutti Jogesh

Abstract

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

Suggested Citation

  • Serinko, Regis J. & Babu, Gutti Jogesh, 1995. "Asymptotics of k-mean clustering under non-i.i.d. sampling," Statistics & Probability Letters, Elsevier, vol. 24(1), pages 57-66, July.
    • Handle: RePEc:eee:stapro:v:24:y:1995:i:1:p:57-66
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    References listed on IDEAS

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    1. Babu, Gutti Jogesh & Singh, Kesar, 1978. "On deviations between empirical and quantile processes for mixing random variables," Journal of Multivariate Analysis, Elsevier, vol. 8(4), pages 532-549, December.
    2. Serinko, Regis J. & Babu, Gutti Jogesh, 1992. "Weak limit theorems for univariate k-mean clustering under a nonregular condition," Journal of Multivariate Analysis, Elsevier, vol. 41(2), pages 273-296, May.
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