| LDR | | | 00000cab a2200000 4500 |
| 001 | | | MAP20260013435 |
| 003 | | | MAP |
| 005 | | | 20260603180814.0 |
| 008 | | | 260428e20260420bel|||p |0|||b|eng d |
| 040 | | | $aMAP$bspa$dMAP |
| 084 | | | $a6 |
| 100 | | | $0MAPA20260008141$aDankwa, Richard |
| 245 | 1 | 0 | $aEnriched truncated exponentiated generalized family of distributions with application to heavy-tailed data$cRichard Dankwa and Kahadawala Cooray |
| 520 | | | $aThe 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 |
| 650 | | 4 | $0MAPA20080579258$aCálculo actuarial |
| 650 | | 4 | $0MAPA20080625535$aDistribuciones de probabilidad |
| 650 | | 4 | $0MAPA20170004592$aColas pesadas |
| 650 | | 4 | $0MAPA20080582951$aTeoría del riesgo |
| 650 | | 4 | $0MAPA20080588953$aAnálisis de riesgos |
| 700 | 1 | | $0MAPA20260008158$aCooray, Kahadawala |
| 710 | 2 | | $0MAPA20100017661$aInternational Actuarial Association |
| 773 | 0 | | $wMAP20077000420$g20/04/2026 Volumen 56 Número 2 - abril 2026 , 23 p.$x0515-0361$tAstin bulletin$dBelgium : ASTIN and AFIR Sections of the International Actuarial Association |
