We introduce a new family of univariate and multivariate slash-distributions. Our construction is based on elliptical distributions. We define the new family by means of a stochastic representation as the scale mixture of an elliptically distributed random variable with respect to the power of a...

This work proposes a method to assess the influence of individual observations in the clustering generated by any process that involves random partitions. We call it Similarity Analysis. It basically consists of decomposing the estimated similarity matrix into an intrinsic and an extrinsic part,...

Bayesian estimation of the systematic risk of a share using product partition models (PPM) is considered in this study. The cluster structure of the PPM is used to derive a robust Bayes estimator of beta and also to identify outliers or clusters of observations. The procedure is implemented...

We present a decision theoretic formulation of product partition models (PPMs) that allows a formal treatment of different decision problems such as estimation or hypothesis testing "and" clustering methods simultaneously. A key observation in our construction is the fact that PPMs can be...

The problem of outlier and change-point identification has received considerable attention in traditional linear regression models from both, classical and Bayesian standpoints. In contrast, for the case of regression models with measurement errors, also known as error-in-variables models, the...

We analyse data from a study involving 173 pregnant women. The data are observed values of the "&bgr;" human chorionic gonadotropin hormone measured during the first 80 days of gestational age, including from one up to six longitudinal responses for each woman. The main objective in this study is to...