Berry Esseen bounds for combinatorial central limit theorems and pattern occurrences, using zero and size biasing
Larry Goldstein
Abstract
Berry Esseen type bounds to the normal, based on zero- and size-bias couplings, are derived using Stein's method. The zero biasing bounds are illustrated with an application to combinatorial central limit theorems where the random permutation has either the uniform distribution or one which is constant over permutations with the same cycle type and having no fixed points. The size biasing bounds are applied to the occurrences of fixed relatively ordered sub-sequences (such as rising sequences) in a random permutation, and to the occurrences of patterns, extreme values, and subgraphs on finite graphs.
Create a lesson
Related papers
Sandpile avalanches in two dimensions are finite
Ahmed Bou-Rabee
Markov Chain Convergence in Kernel-Induced Geometry
Oleksii Kachaiev, Luc Brogat-Motte, Silvia Villa et al.
Interacting Stochastic Systems with Agent-Based Sampling and Connection-Based Reinforcement
Yogesh Dahiya, Gursharn Kaur, Neeraja Sahasrabudhe
Dimension-free Markov--Bernstein-type inequality for R2-valued polynomials
Egor Kosov
Initialization-Dependent Solution Selection by the Euler-Maruyama Scheme for a Degenerate SDE
Akihiro Tanaka
Statistical inference for rough Burgers-type stochastic partial differential equations
Simon Chony Acosta Christian Olivera Ciprian Tudor