We determine the mixing time (up to a constant factor) of the Markov chain whose state space consists of n “dots” on the unit interval, wherein a dot is selected uniformly at random and moved to a uniformly random point between its two neighbors. The method involves a two-step coupling for the upper bound, and an unusual probabilistic second-moment argument for the lower.
Markov Chain Monte Carlo algorithms are often used to sample combinatorial structures such as matchi...
We analyze the speed of convergence to stationarity for a specific stochastic system consisting of a...
Let Ω be the set of all m × n matrices, where r i and c j are the sums of entries in row i and colum...
In the past few years we have seen a surge in the theory of finite Markov chains, by way of new tech...
The derivation of the expected time to coupling in a Markov chain and its relation to the expected t...
AbstractThe derivation of the expected time to coupling in a Markov chain and its relation to the ex...
AbstractA measure of the “mixing time” or “time to stationarity” in a finite irreducible discrete ti...
The distribution of the “mixing time” or the “time to stationarity” in a discrete time irreducible M...
AbstractConsider the class of discrete time, general state space Markov chains which satisfy a “unif...
This book is an introduction to the modern approach to the theory of Markov chains. The main goal of...
The focus of the thesis is the convergence of irreducible aperiodic homoge- neous Markov chains with...
For the probabilistic model of shuffling by random transpositions we provide a coupling construction...
This article provides the first procedure for computing a fully data-dependent interval that traps t...
A cladogram is a tree with labelled leaves and unlabelled degree-3 branchpoints. A certain Markov ch...
AbstractIn an earlier paper [J.J. Hunter, Mixing times with applications to perturbed Markov chains,...
Markov Chain Monte Carlo algorithms are often used to sample combinatorial structures such as matchi...
We analyze the speed of convergence to stationarity for a specific stochastic system consisting of a...
Let Ω be the set of all m × n matrices, where r i and c j are the sums of entries in row i and colum...
In the past few years we have seen a surge in the theory of finite Markov chains, by way of new tech...
The derivation of the expected time to coupling in a Markov chain and its relation to the expected t...
AbstractThe derivation of the expected time to coupling in a Markov chain and its relation to the ex...
AbstractA measure of the “mixing time” or “time to stationarity” in a finite irreducible discrete ti...
The distribution of the “mixing time” or the “time to stationarity” in a discrete time irreducible M...
AbstractConsider the class of discrete time, general state space Markov chains which satisfy a “unif...
This book is an introduction to the modern approach to the theory of Markov chains. The main goal of...
The focus of the thesis is the convergence of irreducible aperiodic homoge- neous Markov chains with...
For the probabilistic model of shuffling by random transpositions we provide a coupling construction...
This article provides the first procedure for computing a fully data-dependent interval that traps t...
A cladogram is a tree with labelled leaves and unlabelled degree-3 branchpoints. A certain Markov ch...
AbstractIn an earlier paper [J.J. Hunter, Mixing times with applications to perturbed Markov chains,...
Markov Chain Monte Carlo algorithms are often used to sample combinatorial structures such as matchi...
We analyze the speed of convergence to stationarity for a specific stochastic system consisting of a...
Let Ω be the set of all m × n matrices, where r i and c j are the sums of entries in row i and colum...