Robust Bayesian analysis of heavy-tailed stochastic volatility models using scale mixtures of normal distributions

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The Geometric Birnbaum-Saunders regression model with cure rate

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A stochastic shift model for economically designed charts constrained by the process stage configuration

An economic model including the labor resource and the process stage configuration is proposed to design g charts allowing for all the design parameters to be varied in an adaptive way. A random shift size is considered during the economic design selection. The results obtained for a benchmark of 64 process stage scenarios show that the activities configuration and some process operating parameters influence the selection of the best control chart strategy: to model the random shift size, its exact distribution can be approximately fitted by a discrete distribution obtained from a relatively small sample of historical data. However, an accurate estimation of the inspection costs associated to the SPC activities is far from being achieved. An illustrative example shows the implementation of the proposed economic model in a real industrial case. (C) 2011 Elsevier B.V. All rights reserved.

Real-time monitoring and kinetic parameter estimation of the affinity interaction of jArtinM and rArtinM with peroxidase glycoprotein by the electrogravimetric technique

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The complementary exponential power lifetime model

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Bayesian estimation of generalized exponential distribution under noninformative priors

The generalized exponential distribution, proposed by Gupta and Kundu (1999), is a good alternative to standard lifetime distributions as exponential, Weibull or gamma. Several authors have considered the problem of Bayesian estimation of the parameters of generalized exponential distribution, assuming independent gamma priors and other informative priors. In this paper, we consider a Bayesian analysis of the generalized exponential distribution by assuming the conventional non-informative prior distributions, as Jeffreys and reference prior, to estimate the parameters. These priors are compared with independent gamma priors for both parameters. The comparison is carried out by examining the frequentist coverage probabilities of Bayesian credible intervals. We shown that maximal data information prior implies in an improper posterior distribution for the parameters of a generalized exponential distribution. It is also shown that the choice of a parameter of interest is very important for the reference prior. The different choices lead to different reference priors in this case. Numerical inference is illustrated for the parameters by considering data set of different sizes and using MCMC (Markov Chain Monte Carlo) methods.

Estimation of water transit time in soils under Amazon forest cover using variations in sigma18O values.

In an attempt to estimate the soil-water transit time using the variation in 18O values, a statistical model was used. This model is based on linear regression analysis applied to the values observed for soil water and rain water. The time obtained from these correlations represents the mean time necessary for the water to run from one collecting point to the next.-from Authors

A disease evolution model with uncertain parameters

In this study we consider the SIS epidemiological model (susceptible-infected-susceptible) in which the transmission and recuperation rates are considered fuzzy sets. The concepts of possibility measures and fuzzy expectancy value are used to obtain the basic reproduction value for infected groups with different viral charge.

A two phase flow nonlinear parameter estimation for capillary tube-suction line heat exchanger

Here we present two-phase flow nonlinear parameter estimation for HFC's flow through capillary tube-suction line heat exchangers, commonly used as expansion devices in small refrigeration systems. The simplifying assumptions adopted are: steady state, pure refrigerant, one-dimensional flow, negligible axial heat conduction in the fluid, capillary tube and suction line walls. Additionally, it is considered that the refrigerant is free from oil and both phases are assumed to be at the same pressure, that is, surface tension effects are neglected. Metastable flow effects are also disregarded, and the vapor is assumed to be saturated at the local pressure. The so-called homogeneous model, involving three, first order, ordinary differential equations is applied to analyze the two-phase flow region. Comparison is done with experimental measurements of the mass flow rate and temperature distribution along capillary tubes working with refrigerant HFC-134a in different operating conditions.

Estimation of variances of the effects of incomplete diallels using a matrix approach

A matrix approach is described for assessing the variance of effects in incomplete diallels designs. The method is illustrated by reference to simulated complete and incomplete diallels using different combinations of constraints, average degree of dominance and, for the incomplete diallel, number of hybrids. Our results showed that caution should be taken in working with incomplete diallels under conditions of overdominance because there were changes in the rank of the genotypes when the excluded hybrid had parents with a low frequency of the favorable allele (i.e. the allele which increases expression of a character). The expression described in this paper is a rapid and safe approach to estimate variances and covariances of the effects of contrasts of incomplete diallels. Copyright by the Brazilian Society of Genetics.

Precision of yule-walker methods for the arma spectral model

In this work a new method is proposed of separated estimation for the ARMA spectral model based on the modified Yule-Walker equations and on the least squares method. The proposal of the new method consists of performing an AR filtering in the random process generated obtaining a new random estimate, which will reestimate the ARMA model parameters, given a better spectrum estimate. Some numerical examples will be presented in order to ilustrate the performance of the method proposed, which is evaluated by the relative error and the average variation coefficient.

Estimation of variance components and prediction of breeding values in rubber tree breeding using the REML/BLUP procedure

The present paper deals with estimation of variance components, prediction of breeding values and selection in a population of rubber tree [Hevea brasiliensis (Willd. ex Adr. de Juss.) Müell.-Arg.] from Rio Branco, State of Acre, Brazil. The REML/BLUP (restricted maximum likelihood/best linear unbiased prediction) procedure was applied. For this purpose, 37 rubber tree families were obtained and assessed in a randomized complete block design, with three unbalanced replications. The field trial was carried out at the Experimental Station of UNESP, located in Selvíria, State of Mato Grosso do Sul, Brazil. The quantitative traits evaluated were: girth (G), bark thickness (BT), number of latex vessel rings (NR), and plant height (PH). Given the unbalanced condition of the progeny test, the REML/BLUP procedure was used for estimation. The narrow-sense individual heritability estimates were 0.43 for G, 0.18 for BT, 0.01 for NR, and 0.51 for PH. Two selection strategies were adopted: one short-term (ST - selection intensity of 8.85%) and the other long-term (LT - selection intensity of 26.56%). For G, the estimated genetic gains in relation to the population average were 26.80% and 17.94%, respectively, according to the ST and LT strategies. The effective population sizes were 22.35 and 46.03, respectively. The LT and ST strategies maintained 45.80% and 28.24%, respectively, of the original genetic diversity represented in the progeny test. So, it can be inferred that this population has potential for both breeding and ex situ genetic conservation as a supplier of genetic material for advanced rubber tree breeding programs. Copyright by the Brazilian Society of Genetics.

Genetic effects on preweaning weight gain of Nelore-Hereford calves according to different models and estimation methods

Additive and nonadditive genetic effects on preweaning weight gain (PWG) of a commercial crossbred population were estimated using different genetic models and estimation methods. The data set consisted of 103,445 records on purebred and crossbred Nelore-Hereford calves raised under pasture conditions on farms located in south, southeast, and middle west Brazilian regions. In addition to breed additive and dominance effects, the models including different epistasis covariables were tested. Models considering joint additive and environment (latitude) by genetic effects interactions were also applied. In a first step, analyses were carried out under animal models. In a second step, preadjusted records were analyzed using ordinary least squares (OLS) and ridge regression (RR). The results reinforced evidence that breed additive and dominance effects are not sufficient to explain the observed variability in preweaning traits of Bos taurus x Bos indicus calves, and that genotype x environment interaction plays an important role in the evaluation of crossbred calves. Data were ill-conditioned to estimate the effects of genotype x environment interactions. Models including these effects presented multicolinearity problems. In this case, RR seemed to be a powerful tool for obtaining more plausible and stable estimates. Estimated prediction error variances and variance inflation factors were drastically reduced, and many effects that were not significant under ordinary least squares became significant under RR. Predictions of PWG based on RR estimates were more acceptable from a biological perspective. In temperate and subtropical regions, calves with intermediate genetic compositions (close to 1/2 Nelore) exhibited greater predicted PWG. In the tropics, predicted PWG increased linearly as genotype got closer to Nelore. ©2006 American Society of Animal Science. All rights reserved.

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.

Weight vector estimation of circular arrays of antennas using Artificial Neural Networks

This paper presents a model for the control of the radiation pattern of a circular array of antennas, shaping it to address the radiation beam in the direction of the user, in order to reduce the transmitted power and to attenuate interference. The control of the array is based on Artificial Neural Networks (ANN) of the type RBF (Radial Basis Functions), trained from samples generated by the Wiener equation. The obtained results suggest that the objective was reached.