AbstractSuppose that A=(ai,j) is an n×n real matrix with constant row sums μ. Then the Dobrushin–Deutsch–Zenger (DDZ) bound on the eigenvalues of A other than μ is given by Z(A):=12max1⩽s,t⩽n∑r=1n|as,r-at,r|. When A a transition matrix of a finite homogeneous Markov chain so that μ=1,Z(A) is called the coefficient of ergodicity of the chain as it bounds the asymptotic rate of convergence, namely, max{|λ||λ∈σ(A)⧹{1}}, of the iteration xiT=xi-1TA, to the stationary distribution vector of the chain.In this paper we study the structure of real matrices for which the DDZ bound is sharp. We apply our results to the study of the class of graphs for which the transition matrix arising from a random walk on the graph attains the bound. We also chara...
AbstractWe investigate random walks (Sn)n∈N0 on the nonnegative integers arising from isotropic rand...
In this paper, we study the notion of the Dobrushin ergodicity coefficient for positive contraction...
A d-regular graph has largest or first (adjacency matrix) eigenvalue λ1 = d. Consider for an even d ...
Suppose that A=(ai,j) is an n×n real matrix with constant row sums μ. Then the Dobrushin–Deutsch–Zen...
AbstractSuppose that A=(ai,j) is an n×n real matrix with constant row sums μ. Then the Dobrushin–Deu...
Suppose that T is an n×n stochastic matrix, and denote its directed graph by D(T). The function τ(T)...
AbstractWe consider the class of stochastic matrices M generated in the following way from graphs: i...
summary:In a recent paper the authors proposed a lower bound on $1 - \lambda _i$, where $\lambda _i$...
AbstractFor finite Markov chains the eigenvalues of P can be used to characterize the chain and also...
Given a primitive stochastic matrix, we provide an upper bound on the moduli of its non-Perron eige...
AbstractWe give lower bounds for the smallest eigenvalue of the Laplacian of corresponding undirecte...
In recent years, some interest has been devoted to studying doubly stochastic Markov chains. These c...
AbstractFor a sequence of stochastic matrices we consider conditions for weak ergodicity of infinite...
For an irreducible stochastic matrix T, the Kemeny constant K(T) measures the expected time to mixi...
AbstractLet P be the transition matrix for an n-state, homogeneous, ergodic Markov chain. Set Q=I−P ...
AbstractWe investigate random walks (Sn)n∈N0 on the nonnegative integers arising from isotropic rand...
In this paper, we study the notion of the Dobrushin ergodicity coefficient for positive contraction...
A d-regular graph has largest or first (adjacency matrix) eigenvalue λ1 = d. Consider for an even d ...
Suppose that A=(ai,j) is an n×n real matrix with constant row sums μ. Then the Dobrushin–Deutsch–Zen...
AbstractSuppose that A=(ai,j) is an n×n real matrix with constant row sums μ. Then the Dobrushin–Deu...
Suppose that T is an n×n stochastic matrix, and denote its directed graph by D(T). The function τ(T)...
AbstractWe consider the class of stochastic matrices M generated in the following way from graphs: i...
summary:In a recent paper the authors proposed a lower bound on $1 - \lambda _i$, where $\lambda _i$...
AbstractFor finite Markov chains the eigenvalues of P can be used to characterize the chain and also...
Given a primitive stochastic matrix, we provide an upper bound on the moduli of its non-Perron eige...
AbstractWe give lower bounds for the smallest eigenvalue of the Laplacian of corresponding undirecte...
In recent years, some interest has been devoted to studying doubly stochastic Markov chains. These c...
AbstractFor a sequence of stochastic matrices we consider conditions for weak ergodicity of infinite...
For an irreducible stochastic matrix T, the Kemeny constant K(T) measures the expected time to mixi...
AbstractLet P be the transition matrix for an n-state, homogeneous, ergodic Markov chain. Set Q=I−P ...
AbstractWe investigate random walks (Sn)n∈N0 on the nonnegative integers arising from isotropic rand...
In this paper, we study the notion of the Dobrushin ergodicity coefficient for positive contraction...
A d-regular graph has largest or first (adjacency matrix) eigenvalue λ1 = d. Consider for an even d ...