Hostname: page-component-78c5997874-lj6df Total loading time: 0 Render date: 2024-11-09T14:27:53.108Z Has data issue: false hasContentIssue false

Design problems for the pure birth process

Published online by Cambridge University Press:  01 July 2016

Gerhard Becker*
Affiliation:
University of Göttingen
Götz Kersting*
Affiliation:
University of Frankfurt
*
Postal address: Institute of Mathematical Statistics, University of Göttingen, Lotzestr. 13, D-3400 Göttingen, W. Germany.
∗∗Postal address: Institut für Angew. Mathematik, Universität Frankfurt, Robert-Meyer-Str. 10, D-6000 Frankfurt, W. Germany.

Abstract

Let Y(t) be a pure birth process. If a maximum likelihood estimator of the birth intensity is desired and the number n of observational points and the last observation T are given in advance, it is shown that equidistant sampling is not an optimal procedure. Properties of ‘optimal' designs and the corresponding maximum likelihood estimators are investigated and compared with equidistant and continuous sampling.

Type
Research Article
Copyright
Copyright © Applied Probability Trust 1983 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

This paper is SFB 135 Study No. 7.

References

Aalen, O. O. (1975) Statistical Inference for a Family of Counting Processes. Ph.D. Dissertation, University of California, Berkeley. Reissued by the Institute of Mathematical Statistics, University of Copenhagen.Google Scholar
Aalen, O. O. (1978) Nonparametric inference for a family of counting processes. Ann. Statist. 6, 701726.CrossRefGoogle Scholar
Athreya, K. B. and Keiding, N. (1977) Estimation theory for continuous time branching processes. Sankhya, A39, 101123.Google Scholar
God Ambe, V. P. (1960) An optimum property of regular maximum likelihood estimation. Ann. Math. Statist. 31, 12081212.Google Scholar
Godambe, V. P. and Thompson, M. E. (1978) Some aspects of the theory of estimating equations. J. Statist. Planning Inference 2, 95104.Google Scholar
Hoel, P. G. (1958) Efficiency problems in polynomial estimation. Ann. Math. Statist. 29, 11341145.CrossRefGoogle Scholar
Keiding, N. (1974) Estimation in the birth process. Biometrika 61, 7180.CrossRefGoogle Scholar
Keiding, N. (1975) Maximum likelihood estimation in the birth-and-death process. Ann. Statist. 3, 363372.Google Scholar
Kendall, D. G. (1949) Stochastic processes and population growth. J. R. Statist. Soc. B 11, 230262.Google Scholar
McDunnough, P. and Wolfson, D. B. (1980) Fixed versus random sampling of certain continuous parameter processes. Austral. J. Statist. 22, 4049.CrossRefGoogle Scholar