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

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      <subfield code="a">On fitting probability distribution to univariate grouped actuarial data with both group mean and relative frequencies</subfield>
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      <subfield code="a">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</subfield>
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      <subfield code="g">06/03/2023 Tomo 27 Número 1 - 2023 , p. 185-205</subfield>
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