DSpace Collection:https://sci.ldubgd.edu.ua/jspui/handle/123456789/183872026-06-15T21:58:33Z2026-06-15T21:58:33ZIdentification of Dynamic Regime Transition Models Between Erlang and Exponential DistributionsTuluchenko, H.Ya.Soviak, I.M.Malanchuk, M.I.https://sci.ldubgd.edu.ua/jspui/handle/123456789/183932026-06-15T17:16:44Z2026-06-01T00:00:00ZTitle: Identification of Dynamic Regime Transition Models Between Erlang and Exponential Distributions
Authors: Tuluchenko, H.Ya.; Soviak, I.M.; Malanchuk, M.I.
Abstract: A dynamic model is proposed for transition between Erlang and exponential distributions using a sigmoid weighting function. The model captures Erlang behavior at small values and exponential tails at large values. Parameters are estimated via maximum likelihood, and numerical results on synthetic data show stable estimation and improved fit compared to classical models.
Description: The study presents a dynamic statistical model describing a smooth transition between Erlang and exponential distributions using a sigmoid weighting function. The model enables flexible representation of data with different distributional regimes and heavy-tail behavior. Parameter estimation is performed via the maximum likelihood method, and numerical experiments on synthetic data confirm the effectiveness and improved fitting performance of the proposed approach compared to classical mixture models.2026-06-01T00:00:00Z