Analyzing Multiple Outcomes: Is it Really Worth the use of Multivariate Linear Regression?

In health related research it is common to have multiple outcomes of interest in a single study. These outcomes are often analysed separately, ignoring the correlation between them. One would expect that a multivariate approach would be a more efficient alternative to individual analyses of each outcome. Surprisingly, this is not always the case. In this article we discuss different settings of linear models and compare the multivariate and univariate approaches. We show that for linear regression models, the estimates of the regression parameters associated with covariates that are shared across the outcomes are the same for the multivariate and univariate models while for outcome-specific covariates the multivariate model performs better in terms of efficiency.

An automatic voice pleasantness classification system based on prosodic and acoustic patterns of voice preference

In the last few years the number of systems and devices that use voice based interaction has grown significantly. For a continued use of these systems the interface must be reliable and pleasant in order to provide an optimal user experience. However there are currently very few studies that try to evaluate how good is a voice when the application is a speech based interface. In this paper we present a new automatic voice pleasantness classification system based on prosodic and acoustic patterns of voice preference. Our study is based on a multi-language database composed by female voices. In the objective performance evaluation the system achieved a 7.3% error rate.

A Multiple Criteria Utility-based Approa h for the Unit Commitment with Wind Power and Pumped Storage Hydro

The integration of wind power in eletricity generation brings new challenges to unit commitment due to the random nature of wind speed. For this particular optimisation problem, wind uncertainty has been handled in practice by means of conservative stochastic scenario-based optimisation models, or through additional operating reserve settings. However, generation companies may have different attitudes towards operating costs, load curtailment, or waste of wind energy, when considering the risk caused by wind power variability. Therefore, alternative and possibly more adequate approaches should be explored. This work is divided in two main parts. Firstly we survey the main formulations presented in the literature for the integration of wind power in the unit commitment problem (UCP) and present an alternative model for the wind-thermal unit commitment. We make use of the utility theory concepts to develop a multi-criteria stochastic model. The objectives considered are the minimisation of costs, load curtailment and waste of wind energy. Those are represented by individual utility functions and aggregated in a single additive utility function. This last function is adequately linearised leading to a mixed-integer linear program (MILP) model that can be tackled by general-purpose solvers in order to find the most preferred solution. In the second part we discuss the integration of pumped-storage hydro (PSH) units in the UCP with large wind penetration. Those units can provide extra flexibility by using wind energy to pump and store water in the form of potential energy that can be generated after during peak load periods. PSH units are added to the first model, yielding a MILP model with wind-hydro-thermal coordination. Results showed that the proposed methodology is able to reflect the risk profiles of decision makers for both models. By including PSH units, the results are significantly improved.

Elaboração e estruturação de um modelo de rating interno

Temos vindo a assistir nos últimos anos a uma evolução no que respeita à avaliação do risco de crédito. As constantes alterações de regulamentação bancária, que resultam dos Acordos de Basileia, têm vindo a impor novas normas que condicionam a quantidade e a qualidade do risco de crédito que as Instituições de Crédito podem assumir nos seus balanços. É de grande importância as Instituições de Crédito avaliarem o risco de crédito, as garantias e o custo de capital, pois têm um impacto direto na sua gestão nomeadamente quanto à afetação de recursos e proteção contra perdas. Desta forma, pretende-se com o presente trabalho elaborar e estruturar um modelo de rating interno através de técnicas estatísticas, assim como identificar as variáveis estatisticamente relevantes no modelo considerado. Foi delineada uma metodologia de investigação mista, considerando na primeira parte do trabalho uma pesquisa qualitativa e na segunda parte uma abordagem quantitativa. Através da análise documental, fez-se uma abordagem dos conceitos teóricos e da regulamentação que serve de base ao presente trabalho. No estudo de caso, o modelo de rating interno foi desenvolvido utilizando a técnica estatística designada de regressão linear múltipla. A amostra considerada foi obtida através da base de dados SABI e é constituída por cem empresas solventes, situadas na zona de Paredes, num horizonte temporal de 2011-2013. A nossa análise baseou-se em três cenários, correspondendo cada cenário aos dados de cada ano (2011, 2012 e 2013). Para validar os pressupostos do modelo foram efetuados testes estatísticos de Durbin Watson e o teste de significância - F (ANOVA). Por fim, para obtermos a classificação de rating de cada variável foi aplicada a técnica dos percentis. Pela análise dos três cenários considerados, verificou-se que o cenário dois foi o que obteve maior coeficiente de determinação. Verificou-se ainda que as variáveis independentes, rácio de liquidez geral, grau de cobertura do ativo total pelo fundo de maneio e rácio de endividamento global são estatisticamente relevantes.