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In this paper, we establish a spatial central limit theorem for a large class of supercritical branching, not necessarily symmetric, Markov processes with spatially dependent branching mechanisms sati...
In this paper we establish spatial central limit theorems for a large class of supercritical branching Markov processes with general spatial-dependent branching mechanisms. These are generalizations o...
In this paper, we establish a spatial central limit theorem for a large class of supercritical branching, not necessarily symmetric, Markov processes with spatially dependent branching mechanisms sati...
In this paper we establish spatial central limit theorems for a large class of supercritical branching Markov processes with general spatial-dependent branching mechanisms. These are generalizations o...
Markov processes are used in a wide range of disciplines including finance.The transition densities of these processes are often unknown. However, the conditionalcharacteristic functions are more like...
A fragmentation of a set $A$ is a graph with vertices labeled by subsets of $A$ which obey a certain parent-child relationship. A random fragmentation tree is a probability distribution on the space o...
Stopping games for symmetric Markov processes
The integrated square error (ISE) and the mean integrated squark error (MISE) for a class of recursive estimators of the transition density function of a vector-valued nonstationary Markov process ...
Let X(t) (ts R,) be an u-self-similar Markov process on Rd or Rd+. The Hausdorff dimension of the image, graph and zero set of X(t) are obtained under certain mild conditions. Similar results are a...
We consider a discrete time periodically correlated process {X.} which is also Markov in the wide sense. We provide closed formulas for the covariance function R (n, m) = EX, X, and for the spectra...
Adap~ve control of discrete time Markov processes with an innnite horizon risk sensitive cost hadionat is investigated. Tfie con~nuityo f the optimal nsk sensitive cost with respect to a parmetes o...
In this paper we study Markov processes never exiting (NE) a subspace A of the state space E or, in other words, Markov processes conditioned to stay in the subspace A. We show bow the knowledge of...
Kernel Estimators for Semi-Markov Processes
Let $xi$ be a subordinator with Laplace exponent $Phi$, $I=int_{0}^{infty}exp(-xi_s)ds$ the so-called exponential functional, and $X$ (respectively, $hat X$) the self-similar Markov process obtained f...

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