f dπ. From the weak law of large numbers we know that the empirical mean nSn = n −1∑n k=1 f(Xk) converges to μ in probability. This result is the working principle behind all Markov chain Monte Carlo… (More)

This paper proposes methods to improve Monte Carlo estimates when the Independent Metropolis-Hastings Algorithm (IMHA) is used. Our first approach uses a control variate based on the sample generated… (More)

Abstract Under a compactness assumption, we show that a φ-irreducible and aperiodic MetropolisHastings chain is geometrically ergodic if and only if its rejection probability is bounded away from… (More)

We consider the problem of estimating the parameter p of a Binomial(n, p) distribution when p lies in the symmetric interval about 1/2 of the form [a, 1 − a], with a ∈ (0, 1/2). For a class of loss… (More)

Nonparametric modeling is an indispensable tool in many applications and its formulation in an hierarchical Bayesian context, using the entire posterior distribution rather than particular… (More)

Distributional findings are obtained relative to various quantities arising in Bernoulli arrays {Xk,j , k ≥ 1, j = 1, . . . , r + 1}, where the rows (Xk,1, . . . , Xk,r+1) are independently… (More)

A recommender system based on ranks is proposed, where an expert’s ranking of a set of objects and a user’s ranking of a subset of those objects are combined to make a prediction of the user’s… (More)

We have introduced a number of modifications to minimize the deleterious effects of cardiopulmonary bypass (CPB) by reducing the surface of the extracorporeal circulation (ECC), the length of the ECC… (More)