In microarray experiments quality often varies, for example between samples and between arrays. The need for quality control is therefore strong. A statistical model and a corresponding analysis method is suggested for experiments with pairing, including designs with individuals observed before...

The performance (accuracy and robustness) of several clustering algorithms is studied for linearly dependent random variables in the presence of noise. It turns out that the error percentage quickly increases when the number of observations is less than the number of variables. This situation is...

In this paper we present a sequential Monte Carlo algorithm for Bayesian sequential experimental design applied to generalised non-linear models for discrete data. The approach is computationally convenient in that the information of newly observed data can be incorporated through a simple...

Household formation analysis is both a multidimensional economical and statistical problem of great complexity. Since most of the literature tries to incorporate multiple economic aspects, there is, considering the extraordinary practical relevance of the problem, a remarkable gap between theory...

This paper studies the effects of information and communication technologies (ICT) in the school environment on educational achievement. To quantify these effects, the impact is evaluated of a project run by the municipality of Guayaquil, Ecuador, which provides computer-aided instruction in...

In this study, the theory of statistical kernel density estimation has been applied for deriving non-parametric kernel prior to the empirical Bayes which frees the Bayesian inference from subjectivity that has worried some statisticians. For comparing the empirical Bayes based on the kernel...

A method of small-area estimation with a utility function is developed. The utility characterises a policy planned to be implemented in each area, based on the area's estimate of a key quantity. It is shown by simulations that the commonly applied composite and empirical Bayes estimators are...

Estimation of normal mean vector has broad applications such as small area estimation, estimation of nonparametric functions and estimation of wavelet coefficients. In this paper, we propose a new shrinkage estimator based on conditional maximum likelihood estimator incorporating with Stein’s...

We show on an application to small-area statistics that efficient estimation is not always conducive to good policy decisions, because the established inferential procedures have no capacity to incorporate the priorities and preferences of the policy makers and the related consequences of...

This report presents participation rate estimates that measure the effectiveness of SNAP from 2005 to 2007 and estimates participation rates for the “working poorâ€â€”those eligible for SNAP who live in households in which someone earned income from a job. It also provides details...