Two-dimensional Sequence Homogeneity Testing Against Mixture Alternative

Authors

  • Irina A. Safaryan Institute for Informatics and Automation Problems of NAS RA
  • Evgueni A. Haroutunian Institute for Informatics and Automation Problems of NAS RA
  • Arsen V. Manasyan Institute for Informatics and Automation Problems of NAS RA

Abstract

The behavior of linear rank statistics is investigated on models in which various subsequences of observations follow different statistical distributions. Such data can be interpreted both as models of a finite number distribution mixtures and as dependence models. We apply data set simulation to obtain estimates of average and variance of used rank statistics. The modeled and asymptotic results are enough close.

References

Lausen B., Shumacher H., " Maximally selected rank statistics", Biometrics, 48, pp. 73-85, 1 992.

Haroutunian E., Safaryan I. "Distributions mixture division with a stratifying parameter", submitted for publication.

Safaryan I., Haroutunian E. "A Common approach to the distributions mixture identification and dependence models analysis", Proceedings of CSIT 2003, pp. 1 84-1 86.

Haroutunian E. and Safaryan I. "Nonparametric consistent estimation of the change moment of random sequence properties", Transactions of Institute for Informatics and Automation Problems of NAS of RA and of YSU, Mathematical P roblems of Computer Science, vol. 17, pp. 76-85, 1997.

Hothorn T., Lausen B., "On the exact distribution of maximally selected rank statistics", Comp. Statist. and Data Anal., vol. 43, pp. 121- 137, 2003.

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Published

2004-05-26

How to Cite

Safaryan, I. A., Haroutunian, E. A., & Manasyan, A. V. (2004). Two-dimensional Sequence Homogeneity Testing Against Mixture Alternative. Mathematical Problems of Computer Science, 23, 67–79. Retrieved from http://mpcs.sci.am/index.php/mpcs/article/view/602

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