Periodic poisson processes and almost-lack-of-memory distributions

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.

Presented by the member of Editorial Board: V. M. Vishnevsky