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We consider chains whose transition probabilities depend on the whole past, with summable continuity rates. We show that Ornstein's
-distance between one such chain and its canonical Markov approximations of different orders is at worst proportional to the continuity rate of the...
In this paper, we introduce nonparametric ARMA models which provide an alternative to nonparametric autoregressive models, when there is a large dependence to the past observations. Conditions for ergodicity and geometric ergodicity are given when both the nonparametric autoregressive part and...
We review the hydrodynamics and discuss the shock, rarefaction fan and contact discontinuity at a microscopic level for a one-dimensional totally asymmetric k-step exclusion process. In particular we define a microscopical object that identifies the shock in the decreasing case.
The contact process on a homogeneous tree of degree 3 or larger is known to have two survival phases: weak and strong. In the weak survival phase, the "Malthusian parameter" (the Hausdorff dimension of the set of ends of the tree in which the infection survives) is less than half the Hausdorff...
This primer provides a self-contained exposition of the case where spatial birth-and-death processes are used for perfect simulation of locally stable point processes. Particularly, a simple dominating coupling from the past (CFTP) algorithm and the CFTP algorithms introduced in , , and...
In a recent paper  we proposed a stochastic algorithm which generates optimal probabilities for the decompression of an image represented by the fixed point of an IFS system (SAOP). We show here that such an algorithm is in fact a non trivial example of Generalized Random System with...
The concern is with the properties of stochastic differential equations (SDEs) describing the motion of particles in 3 dimensional space, on the sphere or in the plane. There is consideration of the case where the drift function comes from a potential function. There is study of SDEs whose...
Let P(x, dy) = t (x, y)ν(d y) be the transition kernel of a Markov chain, where t (x, y) is a density with respect to a σ-finite measure ν on (E,ℰ), with E ⊂ R
. In this note, we propose a general class of estimates for t (x, y) that are strongly consistent and that extend the classical...
We present a new class of one-dimensional particle systems, in which the number of components may change in the process of interaction. We suggest that some of these systems display spontaneous symmetry breaking.
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