83 citations · 103 across the 11 of their papers we have counts for
8 papers · 1 filter
Gold standard process Markovian poisoning: a semiparametric approach
Claire Lacour, Pierre Vandekerkhove
We consider in this paper a stochastic process that mixes in time, according to a nonobserved stationary Markov selection process, two separate sources of randomness: i) a stationa…
Semiparametric topographical mixture models with symmetric errors
Cristina Butucea, Rodrigue Ngueyep Tzoumpe, Pierre Vandekerkhove
Motivated by the analysis of a Positron Emission Tomography (PET) imaging data considered in Bowen et al. (2012), we introduce a semiparametric topographical mixture model able to…
Estimation of a semiparametric contaminated regression model
Pierre Vandekerkhove
We consider in this paper a contamined regression model where the distribution of the contaminating component is known when the Eu- clidean parameters of the regression model, the…
Semiparametric mixtures of symmetric distributions
Cristina Butucea, Pierre Vandekerkhove
We consider in this paper the semiparametric mixture of two distributions equal up to a shift parameter. The model is said to be semiparametric in the sense that the mixed distribu…
A simple variance inequality for U-statistics of a Markov chain with applications
Gersende Fort, Eric Moulines, Pierre Priouret +1
We establish a simple variance inequality for U-statistics whose underlying sequence of random variables is an ergodic Markov Chain. The constants in this inequality are explicit a…
A central limit theorem for adaptive and interacting Markov chains
Gersende Fort, Eric Moulines, Pierre Priouret +1
Adaptive and interacting Markov Chains Monte Carlo (MCMC) algorithms are a novel class of non-Markovian algorithms aimed at improving the simulation efficiency for complicated targ…
Semiparametric estimation of a two-component mixture model
Laurent Bordes, Stéphane Mottelet, Pierre Vandekerkhove
Suppose that univariate data are drawn from a mixture of two distributions that are equal up to a shift parameter. Such a model is known to be nonidentifiable from a nonparametric…
Selection of a MCMC simulation strategy via an entropy convergence criterion
Didier Chauveau, Pierre Vandekerkhove
In MCMC methods, such as the Metropolis-Hastings (MH) algorithm, the Gibbs sampler, or recent adaptive methods, many different strategies can be proposed, often associated in pract…