Decomposition of Multivariate Probabilities
- 1st Edition - September 19, 2014
- Latest edition
- Author: Roger Cuppens
- Editors: Z. W. Birnbaum, E. Lukacs
- Language: English
- Paperback ISBN:9 7 8 - 1 - 4 8 3 2 - 0 4 2 1 - 5
- eBook ISBN:9 7 8 - 1 - 4 8 3 2 - 1 7 6 4 - 2
Decomposition of Multivariate Probability is a nine-chapter text that focuses on the problem of multivariate characteristic functions. After a brief introduction to some useful… Read more
Decomposition of Multivariate Probability is a nine-chapter text that focuses on the problem of multivariate characteristic functions. After a brief introduction to some useful results on measures and integrals, this book goes on dealing with the classical theory and the Fourier-Stieltjes transforms of signed measures. The succeeding chapters explore the multivariate extension of the well-known Paley-Wiener theorem on functions that are entire of exponential type and square-integrable; the theory of infinitely divisible probabilities and the classical results of Hin?in; and the decompositions of analytic characteristic functions. Other chapters are devoted to the important problem of the description of a specific class on n-variate probabilities without indecomposable factors. The final chapter studies the problem of ?-decomposition of multivariate characteristic functions. This book will prove useful to mathematicians and advance undergraduate and graduate students.
Preface
Notation
List of Symbols
Chapter 1 Measures and Integrals
1.1 Measures
1.2 Integrals
1.3 Product Measures
1.4 Signed Measures
1.5 Singular and Absolutely Continuous Measures
1.6 Continuity Sets
Chapter 2 Fourier-Stieltjes Transforms of Signed Measures
2.1 Fourier-Stieltjes Transforms
2.2 Uniqueness Theorem
2.3 Inversion Formulas
2.4 Projection Theorem
2.5 Convolution Theorem
2.6 Continuity Theorems
2.7 Bochner's Theorem
2.8 A Characterization of the Fourier-Stieltjes Transform
2.9 Exponential of Signed Measures
Notes
Chapter 3 Analytic Characteristic Functions
3.1 Examples of Characteristic Functions
3.2 Derivatives of Characteristic Functions
3.3 Analytic Characteristic Functions
3.4 Some Characterization Theorems
3.5 An Extension of the Notion of Analytic Characteristic Functions
3.6 Convex Support of Signed Measures
Notes
Chapter 4 Decomposition Theorems
4.1 Indecomposable Probabilities
4.2 Infinitely Divisible Probabilities
4.3 Canonical Representations
4.4 A Limit Theorem
4.5 Hinčin's Theorem
4.6 Probabilities with No Indecomposable Factor
Notes
Chapter 5 Decomposition Theorems for Analytic Characteristic Functions
5.1 Decompositions of Derivable Characteristic Functions
5.2 Decompositions of Probabilities Belonging to Ar
5.3 Decompositions of Analytic Characteristic Functions
Notes
Chapter 6 Infinitely Divisible Probabilities with Normal Factor
6.1 Case n = 1
6.2 A Necessary Condition
6.3 Induction Method
6.4 Some Sufficient Conditions for Membership to In0
Notes
Chapter 7 Infinitely Divisible Probabilities without Normal Factor
7.1 Probabilities with a Poisson Measure Concentrated on a Strip
7.2 Probabilities Having an Absolutely Continuous Poisson Measure
7.3 Isomorphism Method
7.4 Independent Sets
7.5 Independent Sets and Projections
Notes
Chapter 8 Infinitely Divisible Probabilities with Countable Poisson Spectrum
8.1 The General Case
8.2 Lattice Probabilities
8.3 Extensions to Independent Sets
8.4 Finite Products of Poisson Probabilities
Notes
Chapter 9 α-Decomposition
9.1 Statement of the Problem
9.2 α-Decompositions of Probabilities with Analytic Characteristic Functions
9.3 Probabilities without Indecomposable α-Factors
Notes
Appendix A Some Results of Function Theory
A.1 Stone-Weierstrass Theorem
A.2 Almost Periodic Functions
A.3 Independent Sets
A.4 Analytic Functions
A.5 Topologically Independent Functions
Appendix B Exponentials of Polynomials and Functions
B.1 Case of a Polynomial of One Variable
B.2 Case of a Function of One Variable
B.3 Case of Functions of Several Variables
References
Index
- Edition: 1
- Latest edition
- Published: September 19, 2014
- Language: English
EL
E. Lukacs
Affiliations and expertise
Bowling Green State UniversityRead Decomposition of Multivariate Probabilities on ScienceDirect