Loss Data Analysis : : The Maximum Entropy Approach / / Henryk Gzyl, Silvia Mayoral, Erika Gomes-Gonçalves.

• Superior document: Title is part of eBook package: De Gruyter DG Plus eBook-Package 2018
• VerfasserIn: Gzyl, Henryk,; Gomes-Gonçalves, Erika,; Mayoral, Silvia,
• Place / Publishing House: Berlin ;, Boston : : De Gruyter, , [2018]; ©2018
• Year of Publication: 2018
• Language: English
• Series: De Gruyter STEM
• Physical Description: 1 online resource (XII, 198 p.)
• Other title: Frontmatter --; Preface --; Contents --; 1 Introduction --; 2 Frequency models --; 3 Individual severity models --; 4 Some detailed examples --; 5 Some traditional approaches to the aggregation problem --; 6 Laplace transforms and fractional moment problems --; 7 The standard maximum entropy method --; 8 Extensions of the method of maximum entropy --; 9 Superresolution in maxentropic Laplace transform inversion --; 10 Sample data dependence --; 11 Disentangling frequencies and decompounding losses --; 12 Computations using the maxentropic density --; 13 Review of statistical procedures --; Index --; Bibliography
• Format: Mode of access: Internet via World Wide Web.
• ISBN: 9783110516074; 9783110719550; 9783110604252; 9783110603255; 9783110604191; 9783110603194
• DOI: 10.1515/9783110516074
• Access: restricted access
• Hierarchical level: Monograph
• Statement of Responsibility: Henryk Gzyl, Silvia Mayoral, Erika Gomes-Gonçalves.

This volume deals with two complementary topics. On one hand the book deals with the problem of determining the the probability distribution of a positive compound random variable, a problem which appears in the banking and insurance industries, in many areas of operational research and in reliability problems in the engineering sciences. On the other hand, the methodology proposed to solve such problems, which is based on an application of the maximum entropy method to invert the Laplace transform of the distributions, can be applied to many other problems. The book contains applications to a large variety of problems, including the problem of dependence of the sample data used to estimate empirically the Laplace transform of the random variable. This volume deals with two complementary topics. On one hand the book deals with the problem of determining the the probability distribution of a positive compound random variable, a problem which appears in the banking and insurance industries, in many areas of operational research and in reliability problems in the engineering sciences. On the other hand, the methodology proposed to solve such problems, which is based on an application of the maximum entropy method to invert the Laplace transform of the distributions, can be applied to many other problems. The book contains applications to a large variety of problems, including the problem of dependence of the sample data used to estimate empirically the Laplace transform of the random variable. Contents Introduction Frequency models Individual severity models Some detailed examples Some traditional approaches to the aggregation problem Laplace transforms and fractional moment problems The standard maximum entropy method Extensions of the method of maximum entropy Superresolution in maxentropic Laplace transform inversion Sample data dependence Disentangling frequencies and decompounding losses Computations using the maxentropic density Review of statistical procedures