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  • 1
    Online Resource
    Online Resource
    New York, NY : Springer Science+Business Media, LLC
    UID:
    gbv_662448359
    Format: Online-Ressource
    Edition: 1
    ISBN: 9781441994738
    Series Statement: Springer Series in Operations Research and Financial Engineering 38
    Language: English
    Subjects: Mathematics
    RVK:
    RVK:
    RVK:
    Keywords: Subexponentielle Verteilung ; Wahrscheinlichkeitsverteilung
    URL: Volltext  (lizenzpflichtig)
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  • 2
    Online Resource
    Online Resource
    New York, NY : Springer New York
    UID:
    gbv_1652404805
    Format: Online-Ressource (XI, 157 p. 2 illus, digital)
    Edition: 2nd ed. 2013
    ISBN: 9781461471011
    Series Statement: Springer Series in Operations Research and Financial Engineering
    Content: Preface -- Introduction -- Heavy- and long-tailed distributions -- Subexponential distributions -- Densities and local probabilities -- Maximum of random walks -- References -- Index.
    Content: Heavy-tailed probability distributions are an important component in the modeling of many stochastic systems. They are frequently used to accurately model inputs and outputs of computer and data networks and service facilities such as call centers. They are an essential for describing risk processes in finance and also for insurance premia pricing, and such distributions occur naturally in models of epidemiological spread. The class includes distributions with power law tails such as the Pareto, as well as the lognormal and certain Weibull distributions. One of the highlights of this new edition is that it includes problems at the end of each chapter. Chapter 5 is also updated to include interesting applications to queueing theory, risk, and branching processes. New results are presented in a simple, coherent and systematic way. Graduate students as well as modelers in the fields of finance, insurance, network science and environmental studies will find this book to be an essential reference.
    Note: Description based upon print version of record , Preface to the First Edition; Preface; Contents; Notation and Conventions; Chapter 1 Introduction; Chapter 2 Heavy-Tailed and Long-Tailed Distributions; 2.1 Heavy-Tailed Distributions; 2.2 Characterisation of Heavy-Tailed Distributionsin Terms of Generalised Moments; 2.3 Lower Limit for Tails of Convolutions; 2.4 Long-Tailed Functions and Their Properties; 2.5 Long-Tailed Distributions; 2.6 Long-Tailed Distributions and Integrated Tails; 2.7 Convolutions of Long-Tailed Distributions; 2.8 h-Insensitive Distributions; 2.9 Comments; 2.10 Problems; Chapter 3 Subexponential Distributions , 3.1 Subexponential Distributions on the Positive Half-Line3.2 Subexponential Distributions on the Whole Real Line; 3.3 Subexponentiality and Weak Tail-Equivalence; 3.4 The Class S* of Strong Subexponential Distributions; 3.5 Sufficient Conditions for Subexponentiality; 3.6 Conditions for Subexponentiality in Termsof Truncated Exponential Moments; 3.7 S Is a Proper Subset of L; 3.8 Does FS Imply That FIS?; 3.9 Closure Properties of the Class of Subexponential Distributions; 3.10 Kesten's Bound; 3.11 Subexponentiality and Randomly Stopped Sums; 3.12 Comments; 3.13 Problems , Chapter 4 Densities and Local Probabilities4.1 Long Tailed Densities and Their Convolutions; 4.2 Subexponential Densities on the Positive Half-Line; 4.3 Subexponential Densities on the Real Line; 4.4 Sufficient Conditions for Subexponentiality of Densities; 4.5 bold0mu mumu dotted-Long-Tailed Distributions and Their Convolutions; 4.6 bold0mu mumu dotted-Subexponential Distributions; 4.7 bold0mu mumu dotted-Subexponential Distributions on the Real Line; 4.8 Sufficient Conditions for bold0mu mumu dotted-Subexponentiality; 4.9 Local Asymptotics for a Randomly Stopped Sum , 4.10 Local Subexponentiality of Integrated Tails4.11 Comments; 4.12 Problems; Chapter 5 Maximum of Random Walk; 5.1 Asymptotics for the Maximum of a Random Walkwith a Negative Drift; 5.2 Finite Time Horizon Asymptotics; 5.3 Ladder Structure of Maximum of Random Walk; 5.4 Taboo Renewal Measures; 5.5 Asymptotics for the First Ascending Ladder Height; 5.6 Tail of the Maximum Revisited; 5.7 Local Probabilities of the Maximum; 5.8 Density of the Maximum; 5.9 Explicitly Calculable Ascending Ladder Heights; 5.10 Single Server Queueing System; 5.11 Ruin Probabilities in Cramér-Lundberg Model , 5.12 Subcritical Branching Processes5.13 How Do Large Values of M Occur in Standard Cases?; 5.14 Comments; 5.15 Problems; Answers to Problems; References; Index
    Additional Edition: ISBN 9781461471004
    Additional Edition: Druckausg. Foss, Sergey An introduction to heavy-tailed and subexponential distributions New York : Springer, 2013 ISBN 9781461471004
    Additional Edition: ISBN 9781489988324
    Language: English
    Subjects: Mathematics
    RVK:
    Keywords: Subexponentielle Verteilung ; Subexponentielle Verteilung
    URL: Volltext  (lizenzpflichtig)
    URL: Cover
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  • 3
    UID:
    gbv_845885960
    Format: Online-Ressource (54 p)
    Edition: Online-Ausg.
    ISBN: 1451871368 , 9781451871364
    Series Statement: IMF Working Papers Working Paper No. 08/278
    Content: This is the first of a series of papers that are being written as part of a project to estimate a small quarterly Global Projection Model (GPM). The GPM project is designed to improve the toolkit for studying both own-country and cross-country linkages. In this paper, we estimate a small quarterly projection model of the U.S. economy. The model is estimated with Bayesian techniques, which provide a very efficient way of imposing restrictions to produce both plausible dynamics and sensible forecasting properties. After developing a benchmark model without financial-real linkages, we introduce such linkages into the model and compare the results with and without linkages
    Language: English
    URL: Volltext  (IMF e-Library)
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  • 4
    UID:
    gbv_845886363
    Format: Online-Ressource (59 p)
    Edition: Online-Ausg.
    ISBN: 1451871376 , 9781451871371
    Series Statement: IMF Working Papers Working Paper No. 08/279
    Content: This is the second of a series of papers that are being written as part of a larger project to estimate a small quarterly Global Projection Model (GPM). The GPM project is designed to improve the toolkit for studying both own-country and cross-country linkages. In this paper, we estimate a small quarterly projection model of the US, Euro Area, and Japanese economies. The model is estimated with Bayesian techniques, which provide a very efficient way of imposing restrictions to produce both plausible dynamics and sensible forecasting properties. We show how the model can be used to construct efficient baseline forecasts that incorporate judgment imposed on the near-term outlook
    Language: English
    URL: Volltext  (IMF e-Library)
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  • 5
    UID:
    gbv_845886355
    Format: Online-Ressource (74 p)
    Edition: Online-Ausg.
    ISBN: 1451871384 , 9781451871388
    Series Statement: IMF Working Papers Working Paper No. 08/280
    Content: This is the third of a series of papers that are being written as part of a larger project to estimate a small quarterly Global Projection Model (GPM). The GPM project is designed to improve the toolkit for studying both own-country and cross-country linkages. In this paper, we estimate a small quarterly projection model of the US, Euro Area, and Japanese economies that incorporates oil prices and allows us to trace out the effects of shocks to oil prices. The model is estimated with Bayesian techniques. We show how the model can be used to construct efficient baseline forecasts that incorporate judgment imposed on the near-term outlook
    Language: English
    URL: Volltext  (IMF e-Library)
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