Add to ORKGThe practically important classes of equal-input and of monotone Markov matrices are revisited, with special focus on embeddability, infinite divisibility, and mutual relations. Several uniqueness results for the classic Markov embedding problem are obtained in the process. To achieve our results, we need to employ various algebraic and geometric tools, including commutativity, permutation invariance and convexity. Of particular relevance in several demarcation results are Markov matrices that are idempotents.Comment: 34 pages; revised version with various additions and improvement
AbstractThis paper deals with monotone iterative methods for the computation of the steady-state pro...
Abstract. The standard theorem for stochastic matrices with positive entries is generalized to matri...
International audienceThe Markov commutator associated to a finite Markov kernel P is the convex sem...
The representation problem of finite-dimensional Markov matrices in Markov semigroups is revisited, ...
The embedding problem of Markov chains is a long standing problem where a given stochastic matrix i...
AbstractA stochastic matrix is “monotone” [4] if its row-vectors are stochastically increasing. Clos...
and 4.9. In this handout, we indicate more completely the properties of the eigenvalues of a stochas...
AbstractA subset of the stochastically monotone Markov chains has the property that the expectation ...
A matrical representation of a Markov chain consists of the initial vector and transition matrix of ...
The attached file may be somewhat different from the published versionInternational audienceIn this ...
A stochastic matrix is "monotone" [4] if its row-vectors are stochastically increasing. Closure prop...
L'apendix B (p.163-172) conté el resum de la tesi en catalàThe goal of this thesis is to solve the e...
We establish an equivalence-singularity dichotomy for a large class of one-dimensional Markov measur...
AbstractA classical result of Markov chain theory states that if A is primitive and stochastic then ...
A Markov (or stochastic) matrix is a square matrix whose entries are non-negative and whose column s...
AbstractThis paper deals with monotone iterative methods for the computation of the steady-state pro...
Abstract. The standard theorem for stochastic matrices with positive entries is generalized to matri...
International audienceThe Markov commutator associated to a finite Markov kernel P is the convex sem...
The representation problem of finite-dimensional Markov matrices in Markov semigroups is revisited, ...
The embedding problem of Markov chains is a long standing problem where a given stochastic matrix i...
AbstractA stochastic matrix is “monotone” [4] if its row-vectors are stochastically increasing. Clos...
and 4.9. In this handout, we indicate more completely the properties of the eigenvalues of a stochas...
AbstractA subset of the stochastically monotone Markov chains has the property that the expectation ...
A matrical representation of a Markov chain consists of the initial vector and transition matrix of ...
The attached file may be somewhat different from the published versionInternational audienceIn this ...
A stochastic matrix is "monotone" [4] if its row-vectors are stochastically increasing. Closure prop...
L'apendix B (p.163-172) conté el resum de la tesi en catalàThe goal of this thesis is to solve the e...
We establish an equivalence-singularity dichotomy for a large class of one-dimensional Markov measur...
AbstractA classical result of Markov chain theory states that if A is primitive and stochastic then ...
A Markov (or stochastic) matrix is a square matrix whose entries are non-negative and whose column s...
AbstractThis paper deals with monotone iterative methods for the computation of the steady-state pro...
Abstract. The standard theorem for stochastic matrices with positive entries is generalized to matri...
International audienceThe Markov commutator associated to a finite Markov kernel P is the convex sem...