On Parameter Estimation by Aggregated Poisson Observations
DOI:
https://doi.org/10.52737/18291163-2019.11.5-1-13Keywords:
Parameter estimation, minimum chi-squared estimator, agregated Poisson observations, intensity function, consistency, asymptotic normalityAbstract
We consider the problem of parameter estimation by the observations of inhomogeneous Poisson processes. The intensity function of the process is supposed to be a smooth function with respect to the unknown parameter. We propose a Chi-square statistic on the base of agregated observations and we define a Minimum Chi-square Estimator with the help of this statistics. We show this that estimator is consistent and asymptotically normal. We discuss possible generalizations of the obtained results.
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2019-04-26 — Updated on 2022-09-15
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Copyright (c) 2019 Armenian Journal of Mathematics
This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite
[1]
E. O. Accrachi, C. A. T. Aidara, and A. S. Dabye, “On Parameter Estimation by Aggregated Poisson Observations”, Armen.J.Math., vol. 11, no. 5, pp. 1–13, Sep. 2022, doi: 10.52737/18291163-2019.11.5-1-13.
