Adelaide Figueiredo

Abstract
We propose an approach to cluster and classify compositional data. We transform the compositional data into directional data using the square root transformation. To cluster the compositional data, we apply the identification of a mixture of Watson distributions on the hypersphere and to classify the compositional data into predefined groups, we apply Bayes rules based on the Watson distribution to the directional data. We then compare our clustering results with those obtained in hierarchical clustering and in the K-means clustering using the log-ratio transformations of the data and compare our classification results with those obtained in linear discriminant analysis using log-ratio transformations of the data. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Abstract

Abstract
An important problem in directional statistics is to test the null hypothesis of a common mean direction for several populations. The Analysis of Variance (ANOVA) test for vectorial data may be used to test the hypothesis of the equality of the mean directions for several von Mises-Fisher populations. As this test is valid only for large concentrations, we propose in this paper to apply the resampling techniques of bootstrap and permutation to the ANOVA test. We carried out an extensive simulation study in order to evaluate the performance of the ANOVA test with the resampling techniques, for several sphere dimensions and different sample sizes and we compare with the usual ANOVA test for data from von Mises-Fisher populations. The purpose of this simulation study is also to investigate whether the proposed tests are preferable to the ANOVA test, for low concentrations and small samples. Finally, we present an example with spherical data.

Abstract
The subprime crisis was a global financial crisis that affected a large number of countries and, in particular, the European economies. In this paper we considered fourteen variables associated to the public, private and financial sectors, in order to analyze the main vulnerabilities, differences and similarities observed in twenty-seven European countries. The statistical analysis was performed with the STATIS methodology, with data collected in the period 2002-2011, including some years before and some after the historical crisis of 2007-2008. The study led us to conclude that European countries are different in which concerns to investment, savings, sustainability of public accounts and public investment.

Abstract
This paper compares the export promotion system of advanced and emerging economies in fifty countries. Results show that advanced economies offer, on average, more complete export promotion system, i.e. a greater variety of Export Promotion Programs (EPPs) than emerging economies. Advanced countries offer more financial support, informational services, facilitating activities and education and training services. The specific services that contribute most to these differences are also identified, which is important for national export promotion agencies and policy makers to upgrade their offer to firms in order for them to be better prepared for international trade interactions, especially emerging economies.