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Let $X_{1},..,X_{n}$ denote an i.i.d. sample with light tail distribution and $S_{1}^{n}$ denote the sum of its terms; let $a_{n}$ be a real sequence\ going to infinity with $n.$\ In a previous paper ...
We establish an optimal transportation inequality for the Poisson measure on the configuration space. Furthermore, under the Dobrushin uniqueness condition, we obtain a sharp transportation inequality...
In this paper, we introduce the notion of efficiency (consistency) and examine some asymptotic properties of Markov chain Monte Carlo methods. We apply these results to the Gibbs sampler for independe...
We provide a representation of reversible-jump Markov chain Monte Carlo as Gibbs sampling with alternating updates of a model indicator and a "palette" of parameters we denote $\bm \psi$. A key innova...
The inspection of residuals is a fundamental step to investigate the quality of adjustment of a parametric model to data. For spatial point processes, the concept of residuals has been recently prop...
We consider various versions of adaptive Gibbs and Metropolis- within-Gibbs samplers, which update their selection probabilities (and per- haps also their proposal distributions) on the fly during a...
Gibbs random fields (GRF) are polymorphous statistical models that can be used to analyse different types of dependence, in particular for spatially correlated data. However, when tho...
Delayed Response in Bivariate Set Up Using Gibbs Sampler。
This note presents a simple and elegant sampler which could be used as an alternative to the reversible jump MCMC methodology.
We study fragmentation trees of Gibbs type. In the binary case, we identify the most general Gibbs-type fragmentation tree with Aldous’ beta-splitting model, which has an extended parameter range β >...
We give families of examples where sharp rates of convergence to stationarity of the widely used Gibbs sampler are available. The examples involve standard exponential families and their conjugate ...
Let K be a reversible Markov kernel on a measurable space (S,B) with stationary distribution P. Regard K as a linear operator, K:L2(P)→L2(P), and suppose that L2(P) admits an orthonormal basis of ...
It is a pleasure to congratulate the authors for this excellent, original and pedagogical paper. I read a preliminary draft at the end of 2006 and I then mentioned to the authors that their work sh...
We congratulate the authors on a review of convergence rates for Gibbs sampling routines. Their combined work on studying convergence rates via orthogonal polynomials in the present paper under di...

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