Multiple time series data may exhibit clustering over time and the clustering effect may change across different series. This paper is motivated by the Bayesian non-parametric modelling of the dependence between clustering effects in multiple time series analysis. We follow a Dirichlet process...

This chapter reviews different methods to construct density forecasts and to aggregate forecasts from many sources. Density evaluation tools to measure the accuracy of density forecasts are reviewed and calibration methods for improving the accuracy of forecasts are presented. The manuscript...

We analyze a class of smoothing transformations on probability measures in multiple space dimensions. Applying a synthesis of probabilistic methods and Fourier analysis, we prove existence and uniqueness of a fixed point inside the class of probability measures of finite second moment,...

This article introduces estimators defined as minimizers of Kantorovich distances between statistical models and empirical distributions. Existence, measurability and consistency of these estimators are studied. A few significant examples illustrate the applicability of the theoretical results...

Consistency of minimum divergence estimators, based on grouped data, is studied under conditions which, to our knowledge, are weaker than the ones considered in the existing literature. Comments on the hypotheses and the interpretation of the main results are made, and an illustrative example is...