On fitting probability distribution to univariate grouped actuarial data with both group mean and relative frequencies

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<dc:creator>Khemka, Gaurav</dc:creator>
<dc:creator>Pitt, David</dc:creator>
<dc:creator>Zhang, Jinhui</dc:creator>
<dc:date>2023-03-06</dc:date>
<dc:description xml:lang="es">Sumario: This article compares the relative performance of three methods of inference using distributions suitable for actuarial applications, particularly those that are right-skewed, heavy-tailed, and left-truncated. We compare the traditional maximum likelihood method, which only considers the group limits and frequency of observations in each group, to two research innovations: a modified maximum likelihood method and a modified generalized method of moments approach, both of which incorporate additional group mean information
in the estimation process. We perform a simulation study where the proposed methods outperform the traditional maximum likelihood method and the maximum entropy when the true underlying distribution is both known and unknown</dc:description>
<dc:identifier>https://documentacion.fundacionmapfre.org/documentacion/publico/es/bib/183280.do</dc:identifier>
<dc:language>spa</dc:language>
<dc:rights xml:lang="es">InC - http://rightsstatements.org/vocab/InC/1.0/</dc:rights>
<dc:subject xml:lang="es">Cálculo actuarial</dc:subject>
<dc:subject xml:lang="es">Análisis probabilísticos</dc:subject>
<dc:subject xml:lang="es">Métodos actuariales</dc:subject>
<dc:type xml:lang="es">Artículos y capítulos</dc:type>
<dc:title xml:lang="es">On fitting probability distribution to univariate grouped actuarial data with both group mean and relative frequencies</dc:title>
<dc:relation xml:lang="es">En: North American actuarial journal. - Schaumburg : Society of Actuaries, 1997- = ISSN 1092-0277. - 06/03/2023 Tomo 27 Número 1 - 2023 , p. 185-205</dc:relation>
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