Enriched truncated exponentiated generalized family of distributions with application to heavy-tailed data

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<title>Enriched truncated exponentiated generalized family of distributions with application to heavy-tailed data</title>
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<name type="personal" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20260008158">
<namePart>Cooray, Kahadawala</namePart>
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<namePart>International Actuarial Association</namePart>
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<abstract displayLabel="Summary">The article introduces the Enriched Truncated Exponentiated Generalized (ETE-G) family of distributions for modeling heavy-tailed data, with particular application to insurance loss modeling. A three-parameter sub-model based on the log-logistic distribution (ETELL) is developed and its statistical properties are derived. Parameter estimation is addressed using maximum likelihood methods, and tail behavior is analyzed through tail index and moment conditions. The proposed models are applied to Norwegian fire insurance claims data, demonstrating superior goodness-of-fit compared with traditional Pareto-type distributions. The results highlight the relevance of the ETE-G family for actuarial risk measurement and extreme value analysis</abstract>
<note type="statement of responsibility">Richard Dankwa and Kahadawala Cooray</note>
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<topic>Cálculo actuarial</topic>
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<topic>Distribuciones de probabilidad</topic>
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<topic>Colas pesadas</topic>
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<topic>Teoría del riesgo</topic>
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<topic>Análisis de riesgos</topic>
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<title>Astin bulletin</title>
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<publisher>Belgium : ASTIN and AFIR Sections of the International Actuarial Association</publisher>
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<identifier type="issn">0515-0361</identifier>
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<text>20/04/2026 Volumen 56 Número 2 - abril 2026 , 23 p.</text>
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