misiewicz jolanta (28 Ergebnisse)

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Taschenbuch. Zustand: Neu. Simulating stable, substable and weakly stable random vectors | Jolanta Misiewicz | Taschenbuch | 136 S. | Englisch | 2014 | LAP LAMBERT Academic Publishing | EAN 9783659532207 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This concise textbook covers the full scope of an introductory course in modern probability theory, from elementary combinatorial methods to the central limit theorem, while maintaining mathematical rigor. It includes key topics like the measure extension and the Radon-Nikodym theorems. Designed for a one-semester course, it is well-suited for theoretical mathematics, financial mathematics, insurance, or stochastic modeling students. With 375 exercises, it offers ample opportunities for study and review.

Taschenbuch. Zustand: Neu. A One-Semester Course on Probability | Jolanta Misiewicz | Taschenbuch | Springer Undergraduate Mathematics Series | xii | Englisch | 2025 | Springer | EAN 9783031866807 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

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Hardback. Zustand: New. This title is written for the numerate nonspecialist, and hopes to serve three purposes. First it gathers mathematical material from diverse but related fields of order statistics, records, extreme value theory, majorization, regular variation and subexponentiality. All of these are relevant for understanding fat tails, but they are not, to our knowledge, brought together in a single source for the target readership. Proofs that give insight are included, but for most fussy calculations the reader is referred to the excellent sources referenced in the text. Multivariate extremes are not treated. This allows us to present material spread over hundreds of pages in specialist texts in twenty pages. Chapter 5 develops new material on heavy tail diagnostics and gives more mathematical detail. Since variances and covariances may not exist for heavy tailed joint distributions, Chapter 6 reviews dependence concepts for certain classes of heavy tailed joint distributions, with a view to regressing heavy tailed variables. Second, it presents a new measure of obesity. The most popular definitions in terms of regular variation and subexponentiality invoke putative properties that hold at infinity, and this complicates any empirical estimate. Each definition captures some but not all of the intuitions associated with tail heaviness. Chapter 5 studies two candidate indices of tail heaviness based on the tendency of the mean excess plot to collapse as data are aggregated. The probability that the largest value is more than twice the second largest has intuitive appeal but its estimator has very poor accuracy. The Obesity index is defined for a positive random variable X as: Ob(X) = P (X1 +X4 X2 +X3 X1 ? X2 ? X3 ? X4), Xi independent copies of X. For empirical distributions, obesity is defined by bootstrapping. This index reasonably captures intuitions of tail heaviness. Among its properties, if ? 1 then Ob(X) Third and most important, we hope to convince the reader that fat tail phenomena pose real problems; they are really out there and they seriously challenge our usual ways of thinking about historical averages, outliers, trends, regression coefficients and confidence bounds among many other things. Data on flood insurance claims, crop loss claims, hospital discharge bills, precipitation and damages and fatalities from natural catastrophes drive this point home. While most fat tailed distributions are "bad", research in fat tails is one distribution whose tail will hopefully get fatter.

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Hardback. Zustand: New. This title is written for the numerate nonspecialist, and hopes to serve three purposes. First it gathers mathematical material from diverse but related fields of order statistics, records, extreme value theory, majorization, regular variation and subexponentiality. All of these are relevant for understanding fat tails, but they are not, to our knowledge, brought together in a single source for the target readership. Proofs that give insight are included, but for most fussy calculations the reader is referred to the excellent sources referenced in the text. Multivariate extremes are not treated. This allows us to present material spread over hundreds of pages in specialist texts in twenty pages. Chapter 5 develops new material on heavy tail diagnostics and gives more mathematical detail. Since variances and covariances may not exist for heavy tailed joint distributions, Chapter 6 reviews dependence concepts for certain classes of heavy tailed joint distributions, with a view to regressing heavy tailed variables. Second, it presents a new measure of obesity. The most popular definitions in terms of regular variation and subexponentiality invoke putative properties that hold at infinity, and this complicates any empirical estimate. Each definition captures some but not all of the intuitions associated with tail heaviness. Chapter 5 studies two candidate indices of tail heaviness based on the tendency of the mean excess plot to collapse as data are aggregated. The probability that the largest value is more than twice the second largest has intuitive appeal but its estimator has very poor accuracy. The Obesity index is defined for a positive random variable X as: Ob(X) = P (X1 +X4 X2 +X3 X1 ? X2 ? X3 ? X4), Xi independent copies of X. For empirical distributions, obesity is defined by bootstrapping. This index reasonably captures intuitions of tail heaviness. Among its properties, if ? 1 then Ob(X) Third and most important, we hope to convince the reader that fat tail phenomena pose real problems; they are really out there and they seriously challenge our usual ways of thinking about historical averages, outliers, trends, regression coefficients and confidence bounds among many other things. Data on flood insurance claims, crop loss claims, hospital discharge bills, precipitation and damages and fatalities from natural catastrophes drive this point home. While most fat tailed distributions are "bad", research in fat tails is one distribution whose tail will hopefully get fatter.

Paperback. Zustand: Brand New. 217 pages. 9.25x6.10x9.21 inches. In Stock.

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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -We describe in this book stable, sub-stable and the most general class of weakly stable distributions and processes, which seem to be good candidates for use in stochastic modeling in many areas. In the firs chapter we recall basic properties of characteristic functions for random variables and vectors. By norm-dependent characteristic functions we describe norm-dependent positive definite matrices, which are extensively used in stochastic modeling random vectors with fixed correlation structure. The second chapter contains five definitions of stable variables together with proofs of their equivalence. Next we give few representation involving much simpler random variables. Fourth chapter contains a description of stable vectors and their spectral representation. We recall covariation function and covariation ratio - parameters describing the dependence structure of symmetric stable vectors. In the last chapter we talk about much less known weakly stable vectors. We give detailed proofs of their properties. In section 6 we talk about elliptically symmetric and 1-dependent vectors together with the Cambanis, Keener and Simons construction. 136 pp. Englisch.

Zustand: New. Print on Demand pp. 136 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam.

Zustand: New. PRINT ON DEMAND pp. 136.

Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This concise textbook covers the full scope of an introductory course in modern probability theory, from elementary combinatorial methods to the central limit theorem, while maintaining mathematical rigor. It includes key topics like the measure extension and the Radon-Nikodym theorems. Designed for a one-semester course, it is well-suited for theoretical mathematics, financial mathematics, insurance, or stochastic modeling students. With 375 exercises, it offers ample opportunities for study and review. 220 pp. Englisch.

Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Misiewicz JolantaJolanta K. Misiewicz, born 10.04.1953, Master 1978, PhD 1981, habilitation 1997 - in Probability Theory and Stochastic Processes. Professor since 2007.1978-1998 at Math. Inst. Wroclaw Technical University, then Unive.

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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -We describe in this book stable, sub-stable and the most general class of weakly stable distributions and processes, which seem to be good candidates for use in stochastic modeling in many areas. In the firs chapter we recall basic properties of characteristic functions for random variables and vectors. By norm-dependent characteristic functions we describe norm-dependent positive definite matrices, which are extensively used in stochastic modeling random vectors with fixed correlation structure. The second chapter contains five definitions of stable variables together with proofs of their equivalence. Next we give few representation involving much simpler random variables. Fourth chapter contains a description of stable vectors and their spectral representation. We recall covariation function and covariation ratio - parameters describing the dependence structure of symmetric stable vectors. In the last chapter we talk about much less known weakly stable vectors. We give detailed proofs of their properties. In section 6 we talk about elliptically symmetric and 1-dependent vectors together with the Cambanis, Keener and Simons construction.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 136 pp. Englisch.

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - We describe in this book stable, sub-stable and the most general class of weakly stable distributions and processes, which seem to be good candidates for use in stochastic modeling in many areas. In the firs chapter we recall basic properties of characteristic functions for random variables and vectors. By norm-dependent characteristic functions we describe norm-dependent positive definite matrices, which are extensively used in stochastic modeling random vectors with fixed correlation structure. The second chapter contains five definitions of stable variables together with proofs of their equivalence. Next we give few representation involving much simpler random variables. Fourth chapter contains a description of stable vectors and their spectral representation. We recall covariation function and covariation ratio - parameters describing the dependence structure of symmetric stable vectors. In the last chapter we talk about much less known weakly stable vectors. We give detailed proofs of their properties. In section 6 we talk about elliptically symmetric and 1-dependent vectors together with the Cambanis, Keener and Simons construction.

Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.

Paperback. Zustand: new. Paperback. This concise textbook covers the full scope of an introductory course in modern probability theory, from elementary combinatorial methods to the central limit theorem, while maintaining mathematical rigor. It includes key topics like the measure extension and the Radon-Nikodym theorems. Designed for a one-semester course, it is well-suited for theoretical mathematics, financial mathematics, insurance, or stochastic modeling students. With 375 exercises, it offers ample opportunities for study and review. mso-bidi-theme-font: minor-latin;">This concise textbook covers the full scope of an introductory course in modern probability theory, from elementary combinatorial methods to the central limit theorem, while maintaining mathematical rigor. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This concise textbook covers the full scope of an introductory course in modern probability theory, from elementary combinatorial methods to the central limit theorem, while maintaining mathematical rigor. It includes key topics like the measure extension and the Radon-Nikodym theorems. Designed for a one-semester course, it is well-suited for theoretical mathematics, financial mathematics, insurance, or stochastic modeling students. With 375 exercises, it offers ample opportunities for study and review.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 220 pp. Englisch.