Abstract
Certain characterization properties of time-varying periodic Poisson flows are studied in terms of almost-lack-of-memory (ALM) distributions. Parameter estimation formulas are derived. A method for verifying the hypothesis on the membership of a sample to the class of ALM-distributions is developed. Algorithms for computing critical levels and power of the likelihood ratio test by the Monte Carlo method are designed.
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Dimitrov, B.N., Rykov, V.V. & Krougly, Z.L. Periodic Poisson Processes and Almost-lack-of-memory Distributions. Automation and Remote Control 65, 1597–1610 (2004). https://doi.org/10.1023/B:AURC.0000044269.32890.3e
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DOI: https://doi.org/10.1023/B:AURC.0000044269.32890.3e