We investigate how the stationary distribution of a Markov chain changes when transitions from a single state are modified. In particular, adding a single directed edge to nearest neighbor random walk on a finite discrete torus in dimensions one, two, or three changes the stationary distribution linearly, logarithmically, or only locally. Related results are derived for birth and death chains approximating Bessel diffusions and for random walk on the Sierpinski gasket
The extremes of a univariate Markov chain with regulary varying stationary marginal distribution and...
The extremes of a univariate Markov chain with regulary varying stationary marginal distribution and...
We consider continuous-time Markov chains on integers which allow transitions to adjacent states onl...
A Markov chain is a system consisting of finitely many states and a set of probabilities that dictat...
AbstractTechniques for updating the stationary distribution of a finite irreducible Markov chain fol...
We study Markov chains on a lattice in a codimension-one stratified independent random environment, ...
AbstractWe study the asymptotic behaviour of Markov chains (Xn,ηn) on Z+×S, where Z+ is the non-nega...
. Let \Gamma act on a countable set V with only finitely many orbits. Given a \Gamma-invariant rando...
A random walk is a basic stochastic process on graphs and a key primitive in the design of distribut...
AbstractFor finite irreducible discrete time Markov chains, whose transition probabilities are subje...
M.Sc. (Mathematics)In chapter 1, we give the reader some background concerning digraphs that are use...
In this thesis, we study transition probability estimates for Markov chains and their relationship t...
AbstractA fluctuation theory for Markov chains on an ordered countable state space is developed, usi...
We review results on linearly edge-reinforced random walks. On finite graphs, the process has the sa...
We show that the stationary distribution of a finite Markov chain can be expressed as the sum of cer...
The extremes of a univariate Markov chain with regulary varying stationary marginal distribution and...
The extremes of a univariate Markov chain with regulary varying stationary marginal distribution and...
We consider continuous-time Markov chains on integers which allow transitions to adjacent states onl...
A Markov chain is a system consisting of finitely many states and a set of probabilities that dictat...
AbstractTechniques for updating the stationary distribution of a finite irreducible Markov chain fol...
We study Markov chains on a lattice in a codimension-one stratified independent random environment, ...
AbstractWe study the asymptotic behaviour of Markov chains (Xn,ηn) on Z+×S, where Z+ is the non-nega...
. Let \Gamma act on a countable set V with only finitely many orbits. Given a \Gamma-invariant rando...
A random walk is a basic stochastic process on graphs and a key primitive in the design of distribut...
AbstractFor finite irreducible discrete time Markov chains, whose transition probabilities are subje...
M.Sc. (Mathematics)In chapter 1, we give the reader some background concerning digraphs that are use...
In this thesis, we study transition probability estimates for Markov chains and their relationship t...
AbstractA fluctuation theory for Markov chains on an ordered countable state space is developed, usi...
We review results on linearly edge-reinforced random walks. On finite graphs, the process has the sa...
We show that the stationary distribution of a finite Markov chain can be expressed as the sum of cer...
The extremes of a univariate Markov chain with regulary varying stationary marginal distribution and...
The extremes of a univariate Markov chain with regulary varying stationary marginal distribution and...
We consider continuous-time Markov chains on integers which allow transitions to adjacent states onl...