Patrick Hurde - história de vida : um contributo para a história da dança em Portugal, na segunda metade do séc. XX e inicio do séc. XXI

Tese de doutoramento, Estudos Artísticos (Estudos de Teatro), Universidade de Lisboa, Faculdade de Letras.[O documento original encontra-se depositado no Repositório da Universidade de Lisboa]

Enhancing the selection of a model-based clustering with external categorical variables

In cluster analysis, it can be useful to interpret the partition built from the data in the light of external categorical variables which are not directly involved to cluster the data. An approach is proposed in the model-based clustering context to select a number of clusters which both fits the data well and takes advantage of the potential illustrative ability of the external variables. This approach makes use of the integrated joint likelihood of the data and the partitions at hand, namely the model-based partition and the partitions associated to the external variables. It is noteworthy that each mixture model is fitted by the maximum likelihood methodology to the data, excluding the external variables which are used to select a relevant mixture model only. Numerical experiments illustrate the promising behaviour of the derived criterion. © 2014 Springer-Verlag Berlin Heidelberg.

Danny e o profundo mar azul: introdução da técnica da Meisner em Portugal pela Below de Belt Teatro Co.: relatório de estágio

Relatório de Estágio submetidoà Escola Superior de Teatro e Cinemapara cumprimento dos requisitos necessários à obtenção do grau de Mestre em Artes Performativas- especialização em Teatro-Música

Enhancing the selection of a model-based clustering with external categorical variables

In cluster analysis, it can be useful to interpret the partition built from the data in the light of external categorical variables which are not directly involved to cluster the data. An approach is proposed in the model-based clustering context to select a number of clusters which both fits the data well and takes advantage of the potential illustrative ability of the external variables. This approach makes use of the integrated joint likelihood of the data and the partitions at hand, namely the model-based partition and the partitions associated to the external variables. It is noteworthy that each mixture model is fitted by the maximum likelihood methodology to the data, excluding the external variables which are used to select a relevant mixture model only. Numerical experiments illustrate the promising behaviour of the derived criterion.