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We address the problem of identifying linear relations among variables based on noisy measurements. This is a central question in the search for structure in large data sets. Often a key assumption is...
This paper addresses the problem of Monte Carlo approximation of posterior probability distributions. In particular, we have considered a recently proposed technique known as population Monte Carlo (P...
Nonlinear/non-Gaussian ltering has broad applications in many areas of life sciences where either the dynamic is nonlinear and/or the probability density function of un-certain state is non-Gaussian....
On a πps Scheme of Sampling of Two Units。
The finite system scheme for state-dependent interacting multitype branching systems.
In this work, we approximate a diffusion process by its Euler scheme and we study the convergence of the density of the marginal laws. We improve previous estimates especially for small time.
In this note we provide a stochastic method for approximating solutions of ordinary differential equations. To this end, a stochastic variant of the Euler scheme is given by means of Markov chains. Fo...
For estimating the population variance S2y of study variable y, a class of chain estimators of S2y has been proposed in the presence of two auxiliary variables x and z by using known information on po...
Approximate Bayesian computation methods can be used to evaluate posterior distributions without having to calculate likelihoods. In this paper we discuss and apply an approximate Bayesian computation...

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