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Book Categories |
| Preface | ||
| Symmetrized Random Permutations | 1 | |
| Hankel Determinants as Fredholm Determinants | 21 | |
| Universality and Scaling of Zeros on Symplectic Manifolds | 31 | |
| z-Measures on Partitions, Robinson-Schensted-Knuth Correspondence, and [beta] = 2 Random Matrix Ensembles | 71 | |
| Phase Transitions and Random Matrices | 95 | |
| Matrix Model Combinatorics: Applications to Folding and Coloring | 111 | |
| Interrelationships Between Orthogonal, Unitary and Symplectic Matrix Ensembles | 171 | |
| Dual Isomonodromic Tau Functions and Determinants of Integrable Fredholm Operators | 209 | |
| Functional Equations and Electrostatic Models for Orthogonal Polynomials | 225 | |
| Random Words, Toeplitz Determinants, and Integrable Systems I | 245 | |
| Random Permutations and the Discrete Bessel Kernel | 259 | |
| Solvable Matrix Models | 271 | |
| The [tau]-Function for Analytic Curves | 285 | |
| Integration over Angular Variables for Two Coupled Matrices | 301 | |
| Integrable Lattices: Random Matrices and Random Permutations | 321 | |
| SL(2) and z-Measures | 407 | |
| Some Matrix Integrals Related to Knots and Links | 421 |
| Price | Condition | Delivery | Seller | Action |
| $99.99 | Digital |
| WonderClub |
Ryan Ladouceur
reviewed Random Matrix Models and Their Applications on March 24, 2014
Random Matrix Models and Their Applications
An easy read since I finished up a stats course last term (I got to skip most of the math explanations). It was an interesting look at probability and I think it would be a good starter book for those who aren't very well-versed in math. I certainly wish I'd found this when I started learning Probability myself as the examples were so thoroughly explained in essentially layman's terms and everything was very easy to understand.
Also with an example entirely about poisson distribution of chocolate chips in the baking of cookies, how can you go wrong? :P
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