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With the growth of such fields as financial economics, so has the need for a thorough discussion of statistical size distributions. This volume studies the distributional and statistical properties (including characterizations, estimation of parameters, testing hypotheses, and stochastic order operations) of a multitude of distributions which are utilized as models of size and income in economics and actuarial sciences. Paying attention to some often-neglected, less-known distributions, the text offers an abundance of real-world data and interweaves a useful detailed historical survey of the…mehr

Produktbeschreibung
With the growth of such fields as financial economics, so has the need for a thorough discussion of statistical size distributions. This volume studies the distributional and statistical properties (including characterizations, estimation of parameters, testing hypotheses, and stochastic order operations) of a multitude of distributions which are utilized as models of size and income in economics and actuarial sciences. Paying attention to some often-neglected, less-known distributions, the text offers an abundance of real-world data and interweaves a useful detailed historical survey of the subject.
Providing insight into a field of study that is now gaining global importance, this comprehensive treatment of statistical size distributions:
_ Describes in-full more than 25 models
_ Covers Lorenz curves, multimodal, and multivariate distributions
_ Pays specific attention to Italian, and to some degree Japanese sources
_ Emphasizes interrelations among various families
_ Accounts for more than 200 personal papers, theses, and technical reports by the authors, representing over 40 combined years of study and research
_ Opens a formerly European field to the global market
Autorenporträt
CHRISTIAN KLEIBER, PhD, is assistant professor in the Department of Statistics at the University of Dortmund in Germany. SAMUEL KOTZ, PhD, honorary Doctor of Science, is professor and research scholar at the Department of Engineering Management and Systems Engineering at George Washington University in Washington, D.C.