Renouveau religieux et politique au Mozambique: entre permanence, rupture et historicité

La recherche sur le religieux en Afrique s’est beaucoup intéressée, ces vingt dernières années, au phénomène du « renouveau religieux », et elle s’est plutôt penchée sur la question des ruptures et des innovations qui en résultent. Le présent article interroge la réalité ce renouveau et explore, sur la base d’une étude de cas, la question des continuités et des ruptures dans les changements survenus  [1]. Tout d’abord, il s’intéresse à la nature du renouveau religieux au Mozambique ; il examine ensuite les continuités historiques et dénominationnelles existantes au sein du renouveau pour discuter, dans une troisième section, l’impact des transformations religieuses sur la relation entre religion et politique. La conclusion tente, elle, de faire la part entre ruptures et permanences, et d’appréhender la question du renouveau au-delà de cette dichotomie.

Implicit optimality criterion for convex SIP problem with box constrained index set

We consider a convex problem of Semi-Infinite Programming (SIP) with multidimensional index set. In study of this problem we apply the approach suggested in [20] for convex SIP problems with one-dimensional index sets and based on the notions of immobile indices and their immobility orders. For the problem under consideration we formulate optimality conditions that are explicit and have the form of criterion. We compare this criterion with other known optimality conditions for SIP and show its efficiency in the convex case.

Categorical data clustering using a minimum message length criterion

Research on cluster analysis for categorical data continues to develop, new clustering algorithms being proposed. However, in this context, the determination of the number of clusters is rarely addressed. We propose a new approach in which clustering and the estimation of the number of clusters is done simultaneously for categorical data. We assume that the data originate from a finite mixture of multinomial distributions and use a minimum message length criterion (MML) to select the number of clusters (Wallace and Bolton, 1986). For this purpose, we implement an EM-type algorithm (Silvestre et al., 2008) based on the (Figueiredo and Jain, 2002) approach. The novelty of the approach rests on the integration of the model estimation and selection of the number of clusters in a single algorithm, rather than selecting this number based on a set of pre-estimated candidate models. The performance of our approach is compared with the use of Bayesian Information Criterion (BIC) (Schwarz, 1978) and Integrated Completed Likelihood (ICL) (Biernacki et al., 2000) using synthetic data. The obtained results illustrate the capacity of the proposed algorithm to attain the true number of cluster while outperforming BIC and ICL since it is faster, which is especially relevant when dealing with large data sets.