Abstract
We study statistical experiments with random change of time, which transforms a discrete stochastic basis in a continuous one. The adapted stochastic experiments are studied in continuous stochastic basis in the series scheme. The transition to limit by the series parameter generates an approximation of adapted statistical experiments by a diffusion process with evolution.
The average intensity parameter of renewal times are estimated in three different cases: the Poisson renewal process, a stationary renewal process with delay and the general renewal process with Weibull-Gnedenko renewal time distribution.
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Koroliouk, D., Koroliuk, V.S. (2017). Adapted Statistical Experiments with Random Change of Time. In: Rykov, V., Singpurwalla, N., Zubkov, A. (eds) Analytical and Computational Methods in Probability Theory. ACMPT 2017. Lecture Notes in Computer Science(), vol 10684. Springer, Cham. https://doi.org/10.1007/978-3-319-71504-9_43
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DOI: https://doi.org/10.1007/978-3-319-71504-9_43
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