 Loss data analysis: Analysis of the sample dependence in density reconstruction by maxentropic methodsErika Gomes-Gonçalves, Henryk Gzyl () and Silvia Mayoral Insurance: Mathematics and Economics, 2016, vol. 71, issue C, 145-153 Abstract: The problem of determining probability densities of positive random variables from empirical data is important in many fields, in particular in insurance and risk analysis. The method of maximum entropy has proven to be a powerful tool to determine probability densities from a few values of its Laplace transform. This is so even when the amount of data to compute numerically the Laplace transform is small. But in this case, the variability of the reconstruction due to the sample variability in the available data can lead to quite different results. It is the purpose of this note to quantify as much as possible the variability of the densities reconstructed by means of two maxentropic methods: the standard maximum entropy method and its extension to incorporate data with errors. Keywords: Loss distributions; Loss data analysis; Maximum entropy density reconstruction; Sample dependence of density estimation; Sample dependence of risk measures (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:insuma:v:71:y:2016:i:c:p:145-153 DOI: 10.1016/j.insmatheco.2016.08.007 Access Statistics for this article Insurance: Mathematics and Economics is currently edited by R. Kaas, Hansjoerg Albrecher, M. J. Goovaerts and E. S. W. Shiu More articles in Insurance: Mathematics and Economics from Elsevier |
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