Multiple particle and cluster emissions from Zr following intermediate energies photo absorption

A new approach based on a N-a cluster photoabsorption model is proposed for the understanding of the puzzling steady increase behavior of the 90Zr (e, α) yield measured at the National Bureau of Standards (NBS) within the Giant Dipole Resonance and quasideuteron energy range. The calculation takes into account the pre-equilibrium emissions of protons, neutrons and alpha particles in the framework of an extended version of the multicollisional intranuclear cascade model (MCMC). Another Monte Carlo based algorithm describes the statistical decay of the compound nucleus in terms of the competition between particle evaporation (p, n, d, α, 3He and t) and nuclear fission. The results reproduce quite successfully the 90Zr (e,α) yield, suggesting that emissions of a particles are essential for the interpretation of the exotic increase of the cross sections.

Nuclear photoproduction of pseudoscalar mesons at forward angles up to 6.0 GeV

The nuclear incoherent π 0 photoproduction cross section from 12C is evaluated at forward angles in the 4.0 to 6.0 GeV energy range using the multicollisional intranuclear cascade model MCMC. The model incorporates some improvements in comparison with previous versions associated with the momentum distribution (MD) for light nuclei - extracted from the available (e,e ′p) data - as well as the evaluation of the shadowing effects during the photo-nucleus interaction. The final results of the single and double differential cross sections at forward angles are very sensitive to the MD parameterizations due to the Pauli principle, which largely suppresses the cross sections for low momentum transfer. The attenuation of the nuclear cross section due to pion - nucleus final state interactions is approximately 40% (without nuclear shadowing), which is in nice agreement with the predictions from the Glauber model. The single and double π 0 differential cross sections are presented for possible applications for the interpretation of the inelastic background in the PrimEx experiment at the Jefferson Laboratory. © 2007 American Institute of Physics.

Planning accelerated life tests under Exponentiated-Weibull-Arrhenius model

Purpose - The purpose of this paper is to present designs for an accelerated life test (ALT). Design/methodology/approach - Bayesian methods and simulation Monte Carlo Markov Chain (MCMC) methods were used. Findings - In the paper a Bayesian method based on MCMC for ALT under EW distribution (for life time) and Arrhenius models (relating the stress variable and parameters) was proposed. The paper can conclude that it is a reasonable alternative to the classical statistical methods since the implementation of the proposed method is simple, not requiring advanced computational understanding and inferences on the parameters can be made easily. By the predictive density of a future observation, a procedure was developed to plan ALT and also to verify if the conformance fraction of the manufactured process reaches some desired level of quality. This procedure is useful for statistical process control in many industrial applications. Research limitations/implications - The results may be applied in a semiconductor manufacturer. Originality/value - The Exponentiated-Weibull-Arrhenius model has never before been used to plan an ALT. © Emerald Group Publishing Limited.

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.

A bayesian analysis for the parameters of the exponential-logarithmic distribution

The exponential-logarithmic is a new lifetime distribution with decreasing failure rate and interesting applications in the biological and engineering sciences. Thus, a Bayesian analysis of the parameters would be desirable. Bayesian estimation requires the selection of prior distributions for all parameters of the model. In this case, researchers usually seek to choose a prior that has little information on the parameters, allowing the data to be very informative relative to the prior information. Assuming some noninformative prior distributions, we present a Bayesian analysis using Markov Chain Monte Carlo (MCMC) methods. Jeffreys prior is derived for the parameters of exponential-logarithmic distribution and compared with other common priors such as beta, gamma, and uniform distributions. In this article, we show through a simulation study that the maximum likelihood estimate may not exist except under restrictive conditions. In addition, the posterior density is sometimes bimodal when an improper prior density is used. © 2013 Copyright Taylor and Francis Group, LLC.

Análise Bayesiana para a distribuição Exponencial-Logarítmica

Pós-graduação em Matematica Aplicada e Computacional - FCT

Genes de efeito principal e locos de características quantitativas (QTL) em suínos

Pós-graduação em Zootecnia - FMVZ

Análise Bayesiana de dados composicionais na presença de covariáveis

Pós-graduação em Matematica Aplicada e Computacional - FCT

Bayesian inference for two-parameter gamma distribution assuming different noninformative priors

In this paper distinct prior distributions are derived in a Bayesian inference of the two-parameters Gamma distribution. Noniformative priors, such as Jeffreys, reference, MDIP, Tibshirani and an innovative prior based on the copula approach are investigated. We show that the maximal data information prior provides in an improper posterior density and that the different choices of the parameter of interest lead to different reference priors in this case. Based on the simulated data sets, the Bayesian estimates and credible intervals for the unknown parameters are computed and the performance of the prior distributions are evaluated. The Bayesian analysis is conducted using the Markov Chain Monte Carlo (MCMC) methods to generate samples from the posterior distributions under the above priors.

A non-homogeneous poisson model with spatial anisotropy applied to ozone data from Mexico City

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Modelos para dados grupados e sensurados aplicados à área biológica: comparação usando fator de Bayes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

The FGM bivariate lifetime copula model: a bayesian approach

In this paper, we propose a bivariate distribution for the bivariate survival times based on Farlie-Gumbel-Morgenstern copula to model the dependence on a bivariate survival data. The proposed model allows for the presence of censored data and covariates. For inferential purpose a Bayesian approach via Markov Chain Monte Carlo (MCMC) is considered. Further, some discussions on the model selection criteria are given. In order to examine outlying and influential observations, we present a Bayesian case deletion influence diagnostics based on the Kullback-Leibler divergence. The newly developed procedures are illustrated via a simulation study and a real dataset.

Modelos lineares generalizados bayesianos para dados longitudinais

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)