Perplexing Problems in Probability | Festschrift in Honor of Harry Kesten | ISBN 9780817640934

Perplexing Problems in Probability

Festschrift in Honor of Harry Kesten

herausgegeben von Maury Bramson und Richard T. Durrett
Mitwirkende
Herausgegeben vonMaury Bramson
Herausgegeben vonRichard T. Durrett
Buchcover Perplexing Problems in Probability  | EAN 9780817640934 | ISBN 0-8176-4093-2 | ISBN 978-0-8176-4093-4

Perplexing Problems in Probability

Festschrift in Honor of Harry Kesten

herausgegeben von Maury Bramson und Richard T. Durrett
Mitwirkende
Herausgegeben vonMaury Bramson
Herausgegeben vonRichard T. Durrett

Inhaltsverzeichnis

  • 1 Harry Kesten’s Publications: A Personal Perspective.
  • 2 Lattice Trees, Percolation and Super-Brownian Motion.
  • 3 Percolation in ? + 1 Dimensions at the Uniqueness Threshold.
  • 4 Percolation on Transitive Graphs as a Coalescent Process: Relentless Merging Followed by Simultaneous Uniqueness.
  • 5 Inequalities and Entanglements for Percolation and Random-Cluster Models.
  • 6 From Greedy Lattice Animals to Euclidean First-Passage Percolation.
  • 7 Reverse Shapes in First-Passage Percolation and Related Growth Models.
  • 8 Double Behavior of Critical First-Passage Percolation.
  • 9 The van den Berg-Kesten-Reimer Inequality: A Review.
  • 10 Large Scale Degrees and the Number of Spanning Clusters for the Uniform Spanning Tree.
  • 11 On the Absence of Phase Transition in the Monomer-Dimer Model.
  • 12 Loop-Erased Random Walk.
  • 13 Dominance of the Sum over the Maximum and Some New Classes of Stochastic Compactness.
  • 14 Stability and Heavy Traffic Limits for Queueing Networks.
  • 15 Rescaled Particle Systems Converging to Super-Brownian Motion.
  • 16 The Hausdorff Measure of the Range of Super-Brownian Motion.
  • 17 Branching Random Walks on Finite Trees.
  • 18 Toom’s Stability Theorem in Continuous Time.
  • 19 The Role of Explicit Space in Plant Competition Models.
  • 20 Large Deviations for Interacting Particle Systems.
  • 21 The Gibbs Conditioning Principle for Markov Chains.