Identification of Dynamic Regime Transition Models Between Erlang and Exponential Distributions

Tuluchenko, H.Ya.; Soviak, I.M.; Malanchuk, M.I.

Please use this identifier to cite or link to this item: https://sci.ldubgd.edu.ua/jspui/handle/123456789/18393

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DC Field	Value	Language
dc.contributor.author	Tuluchenko, H.Ya.	-
dc.contributor.author	Soviak, I.M.	-
dc.contributor.author	Malanchuk, M.I.	-
dc.date.accessioned	2026-06-15T17:16:44Z	-
dc.date.available	2026-06-15T17:16:44Z	-
dc.date.issued	2026-06	-
dc.identifier.citation	Tuluchenko H. Ya., Soviak I. M., Malanchuk M. I. Identification of Dynamic Regime Transition Models Between Erlang and Exponential Distributions. In: International Conference of Young Mathematicians, The Institute of Mathematics of the National Academy of Sciences of Ukraine, Kyiv, Ukraine, June 3–5, 2026.	en_US
dc.identifier.uri	https://sci.ldubgd.edu.ua/jspui/handle/123456789/18393	-
dc.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.	en_US
dc.description.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.	en_US
dc.language.iso	en	en_US
dc.publisher	International Conference of Young Mathematicians The Institute of Mathematics of the National Academy of Sciences of Ukraine	en_US
dc.relation.ispartofseries	International Conference of Young Mathematicians (ICYM), Proceedings of the Conference, 2026;	-
dc.subject	dynamic mixture model	en_US
dc.subject	Erlang and exponential distributions	en_US
dc.title	Identification of Dynamic Regime Transition Models Between Erlang and Exponential Distributions	en_US
dc.type	Thesis	en_US
Appears in Collections:	2026

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