Modelos estocásticos com heterocedasticidade: Uma abordagem Bayesiana para os retornos do Ibovespa

Current research compares the Bayesian estimates obtained for the parameters of processes of ARCH family with normal and Student's t distributions for the conditional distribution of the return series. A non-informative prior distribution was adopted and a reparameterization of models under analysis was taken into account to map parameters' space into real space. The procedure adopts a normal prior distribution for the transformed parameters. The posterior summaries were obtained by Monte Carlo Markov Chain (MCMC) simulation methods. The methodology was evaluated by a series of Bovespa Index returns and the predictive ordinate criterion was employed to select the best adjustment model to the data. Results show that, as a rule, the proposed Bayesian approach provides satisfactory estimates and that the GARCH process with Student's t distribution adjusted better to the data.

Avaliação de modelos estocásticos no posicionamento GNSS

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Planejamento de reativos em sistemas elétricos de potência multi-área através de modelos estocásticos

Pós-graduação em Engenharia Elétrica - FEIS

Modelos de distribuição espacial de precipitações intensas

Pós-graduação em Física - IGCE

Incorporação de incertezas associadas à predição de modelos hidrológicos aos instrumentos de gestão em recursos hídricos

Water management has in the watershed plans an important tool to plan the territory and adjust the activities develop over it to the natural resources availability. The incorporation of uncertainty analysis associated with hydrological modelling predictions is a manner to simulate scenarios and work with chances and probabilities that certain events happens inside these plans. Using stochastic methods is possible to consider uncertainty from estimations and even model it. Stochastic methods developed considerably during the last 30 years, but its applications to real-world problems have been limited, and did not turn into routine in hydrology. This paper brings an overview from eminent hydrologists about this subject and discuss the Brazilian and Paulista situation in the scope of groundwater monitoring.

Impacto das condições climáticas sobre a etiologia das bacteremias nosocomiais no Hospital das Clínicas da Faculdade de Medicina de Botucatu-UNESP

Pós-graduação em Doenças Tropicais - FMB

Modelo cinético estocástico para a transcrição considerando colisões entre as moléculas de RNA polimerase

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Ictiofauna de riachos na planície costeira da bacia do rio Itanhaém, litorial sul de São Paulo

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Modelo estocástico para dados GNSS e séries temporais de coordenadas GNSS

Pós-graduação em Ciências Cartográficas - FCT

Contextualização deposicional da formação Rio Claro no município de Paulínia/SP empregando simulações estocásticas

The Rio Claro Formation, Tertiary-Quaternary age, is composed of unconsolidated sediments deposited by fluvial systems. In Paulínia (SP) region geological studies comprising sedimentological, structural and geomorphological aspects indicate that the Rio Claro Formation is constituted by deposits of a meandering fluvial system. Data from SPT drillings were used to obtain sedimentary textural information in order to generate stochastic stratigraphic models. Particle size analysis was carried with the core samples which resulted in the distinction of five litofacies, three of which can be grouped into only one mudstone unit. The other two facies represent channel belt facies, being clayey sands and medium to coarse sands. Geostatistical modeling of the stratigraphic architecture followed together with correlation of analogue outcrop data and conceptual models for this type of depositional system. 100 models were generated with the SPT drillings and 50 models were generated with data from an analogue outcrop, which allowed constraining of both simulation sets to the depositional model given for the region. T-PROGS methodology has good applicability in simulating stratigraphic frameworks and its inherent limitations may be approached with parallel studies, such as stochastic modeling of analogue outcrops or geophysical methods