Nicht lieferbar
Andere Kunden interessierten sich auch für
![Data-Driven Science and Engineering]( "Data-Driven Science and Engineering")
Data-Driven Science and Engineering92,99 €![High Performance Computing in Science and Engineering ' 07]( "High Performance Computing in Science and Engineering ' 07")
High Performance Computing in Science and Engineering ' 07111,99 €![Machine Learning]( "Machine Learning")
Machine Learning48,99 €![Data Fusion and Perception]( "Data Fusion and Perception")
Data Fusion and Perception37,99 €![Computer Age Statistical Inference]( "Computer Age Statistical Inference")
Computer Age Statistical Inference107,99 €![An Introduction to Kolmogorov Complexity and Its Applications]( "An Introduction to Kolmogorov Complexity and Its Applications")
An Introduction to Kolmogorov Complexity and Its Applications53,99 €![Laboratory Experiments in Information Retrieval]( "Laboratory Experiments in Information Retrieval")
Laboratory Experiments in Information Retrieval37,99 €
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
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