Computational tools for comparing asymmetric GARCH models via Bayes factors

In this paper we use Markov chain Monte Carlo (MCMC) methods in order to estimate and compare GARCH models from a Bayesian perspective. We allow for possibly heavy tailed and asymmetric distributions in the error term. We use a general method proposed in the literature to introduce skewness into a continuous unimodal and symmetric distribution. For each model we compute an approximation to the marginal likelihood, based on the MCMC output. From these approximations we compute Bayes factors and posterior model probabilities. (C) 2012 IMACS. Published by Elsevier B.V. All rights reserved.

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.

Analytical tools to assess the voltage stability of induction-based distributed generators

The installation of induction distributed generators should be preceded by a careful study in order to determine if the point of common coupling is suitable for transmission of the generated power, keeping acceptable power quality and system stability. In this sense, this paper presents a simple analytical formulation that allows a fast and comprehensive evaluation of the maximum power delivered by the induction generator, without losing voltage stability. Moreover, this formulation can be used to identify voltage stability issues that limit the generator output power. All the formulation is developed by using the equivalent circuit of squirrel-cage induction machine. Simulation results are used to validate the method, which enables the approach to be used as a guide to reduce the simulation efforts necessary to assess the maximum output power and voltage stability of induction generators. (C) 2011 Elsevier Ltd. All rights reserved.