Part I. Basic Concepts: 1. Non-commutative probability spaces and distributions; 2. A case study of non-normal distribution; 3. C*-probability spaces; 4. Non-commutative joint distributions; 5. Definition and basic properties of free independence; 6. Free product of *-probability spaces; 7. Free product of C*-probability spaces; Part II. Cumulants: 8. Motivation: free central limit theorem; 9. Basic combinatorics I: non-crossing partitions; 10. Basic Combinatorics II: M s inversion; 11. Free cumulants: definition and basic properties; 12. Sums of free random variables; 13. More about limit theorems and infinitely divisible distributions; 14. Products of free random variables; 15. R-diagonal elements; Part III. Transforms and Models: 16. The R-transform; 17. The operation of boxed convolution; 18. More on the 1-dimensional boxed convolution; 19. The free commutator; 20. R-cyclic matrices; 21. The full Fock space model for the R-transform; 22. Gaussian Random Matrices; 23. Unitary Random Matrices; Notes and Comments; Bibliography; Index
Summary
This 2006 book is a self-contained introduction to free probability theory suitable for an introductory graduate level course
Notes
Title from publishers bibliographic system (viewed 22 Dec 2011)
