Pseudo-Regularly Varying Functions and Generalized Renewal Processes

Valeriĭ V. Buldygin, Karl-Heinz Indlekofer, Oleg I. Klesov , Josef G. Steinebach

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English

Springer International Publishing AG
25 October 2018

Real analysis, real variables; Differential calculus & equations; Probability & statistics; Stochastics

Series: Probability Theory and Stochastic Modelling

One of the main aims of this book is to exhibit some fruitful links between renewal theory and regular variation of functions. Applications of renewal processes play a key role in actuarial and financial mathematics as well as in engineering, operations research and other fields of applied mathematics. On the other hand, regular variation of functions is a property that features prominently in many fields of mathematics.

The structure of the book reflects the historical development of the authors’ research work and approach – first some applications are discussed, after which a basic theory is created, and finally further applications are provided. The authors present a generalized and unified approach to the asymptotic behavior of renewal processes, involving cases of dependent inter-arrival times. This method works for other important functionals as well, such as first and last exit times or sojourn times (also under dependencies), and it can be used to solve several other problems. For example, various applications in function analysis concerning Abelian and Tauberian theorems can be studied as well as those in studies of the asymptotic behavior of solutions of stochastic differential equations. The classes of functions that are investigated and used in a probabilistic context extend the well-known Karamata theory of regularly varying functions and thus are also of interest in the theory of functions.

The book provides a rigorous treatment of the subject and may serve as an introduction to the field. It is aimed at researchers and students working in probability, the theory of stochastic processes, operations research, mathematical statistics, the theory of functions, analytic number theory and complex analysis, as well as economists with a mathematical background. Readers should have completed introductory courses in analysis and probability theory.

By: Valeriĭ V. Buldygin, Karl-Heinz Indlekofer, Oleg I. Klesov, Josef G. Steinebach
Imprint: Springer International Publishing AG
Country of Publication: Switzerland
Edition: 2018 ed.
Volume: 91
Dimensions: Height: 235mm, Width: 155mm,
Weight: 916g
ISBN: 9783319995366
ISBN 10: 3319995367
Series: Probability Theory and Stochastic Modelling
Pages: 482
Publication Date: 25 October 2018
Audience: Professional and scholarly , College/higher education , Undergraduate , Further / Higher Education
Format: Hardback
Publisher's Status: Active

Valerii Buldygin (1946–2012) received his PhD in Mathematics from Kiev Shevchenko University in 1973, and went on to work at the Institute of Mathematics, which is part of the Academy of Science of Ukraine (1973–1986) and at the National Technical University of Ukraine “Igor Sikorski Kyiv Polytechnic Institute” (1986–2012). His fields of research were probability and statistics with a special emphasis on limit theorems in Banach spaces, matrix normalizations in limit theorems, and asymptotic properties of correlograms and estimators of impulse transfer functions for linear systems. Karl-Heinz Indlekofer received his PhD in Mathematics from the Albert Ludwigs University of Freiburg im Breisgau in 1970. From 1970 to 1974 he worked at the Johann Wolfgang Goethe University of Frankfurt am Main. Since 1974 he has served as a Professor of Mathematics at the University of Paderborn. His field of research is analytic and probabilistic number theory with a special emphasis on sieve methods, limit theorems in number theory and arithmetical semigroups. Oleg I. Klesov received his PhD in Mathematics from Kiev Shevchenko University in 1981. He worked at the same University as a scientific researcher until 1990, when he moved to the National Technical University of Ukraine “Igor Sikorski Kyiv Polytechnic Institute”. His fields of research include probability and stochastic processes with a special emphasis on random fields, limit theorems in probability, and the reconstruction of stochastic processes from discrete observations.Josef G. Steinebach received his PhD in Mathematics from the University of Dusseldorf in 1976. After a visit to Carleton University, Ottawa, in 1980, he worked as a Professor of Mathematics at the Universities of Marburg (1980–1987, 1991–2002), Hannover (1987–1991), and Cologne (since 2002). His field of research is probability and statistics with a special emphasis on change-point analysis, limit theorems in probability, and asymptotic statistics.