High-dimensional spectroscopy data are increasingly common in many fields of science. Building classification models in this context is challenging, due not only to high dimensionality but also to high autocorrelations. A two-stage classification strategy is proposed. First, in a data...

The analysis of short longitudinal series of circular data may be problematic and to some extent has not been fully developed. A Bayesian analysis of a new model for such data is presented. The model is based on a radial projection onto the circle of a particular bivariate normal distribution....

In this paper we propose objective Bayes procedures for model selection. To this end, we follow Gutiérrez-Peña and Walker [Gutiérrez-Peña, E., Walker, S.G., 2005. Statistical decision problems and Bayesian nonparametric methods. International Statistical Review 73, 309-330], who view...

Reference analysis is one of the most successful general methods to derive noninformative prior distributions. In practice, however, reference priors are often difficult to obtain. Recently developed theory for conditionally reducible natural exponential families identifies an attractive...

It is well known that Jeffreys' prior is asymptotically least favorable under the entropy risk, i.e. it asymptotically maximizes the mutual information between the sample and the parameter. However, in this paper we show that the prior that minimizes (subject to certain constraints) the mutual...