Estimating the Structural Distribution Function of Cell Probabilities

Authors

  • Bert van Es University of Amsterdam
  • Chris A.J. Klaassen University of Amsterdam
  • Robert M. Mnatsakanov West Virginia University, Morgantown A. Razmadze Mathematical Institute, Tbilisi

DOI:

https://doi.org/10.17713/ajs.v32i1&2.451

Abstract

We consider estimation of the structural distribution function of the cell probabilities of a multinomial sample in situations where the number of cells is large. We review the performance of the natural estimator, an estimator based on grouping of the cells, and a kernel type estimator. Inconsistency of the natural estimator and weak consistency of the other two estimators is derived by Poissonization and other, new, technical devices.

References

M. Aerts, I. Augustyns, and P. Janssen. Central limit theorem for the total squared error of local polynomial estimators of cell probabilities. J. Statist. Plann. Inference, 91: 181–193, 2000.

E.V. Khmaladze. The statistical analysis of a large number of rare events. Technical report, CWI, Amsterdam, Report MS-R8804, 1988.

E.V. Khmaladze and R.Ya. Chitashvili. Statistical analysis of a large number of rare events and related problems (Russian). Proc. A. Razmadze Math. Inst. Georgian Acad. Sci., Tbilisi, 92:196–245, 1989.

C.A.J. Klaassen and R.M. Mnatsakanov. Consistent estimation of the structural distribution function. Scand. J. Statist., 27:733–746, 2000.

B. van Es and S. Kolios. Estimating a structural distribution function by grouping. Technical report, University of Amsterdam, Mathematics ArXiv PR/0203080, 2002.

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Published

2016-04-03

Issue

Section

Articles

How to Cite

Estimating the Structural Distribution Function of Cell Probabilities. (2016). Austrian Journal of Statistics, 32(1&2), 85–98. https://doi.org/10.17713/ajs.v32i1&2.451