Improved maximum-likelihood estimation in a regression model with general parametrization

We analyse the finite-sample behaviour of two second-order bias-corrected alternatives to the maximum-likelihood estimator of the parameters in a multivariate normal regression model with general parametrization proposed by Patriota and Lemonte [A. G. Patriota and A. J. Lemonte, Bias correction in a multivariate regression model with genereal parameterization, Stat. Prob. Lett. 79 (2009), pp. 1655-1662]. The two finite-sample corrections we consider are the conventional second-order bias-corrected estimator and the bootstrap bias correction. We present the numerical results comparing the performance of these estimators. Our results reveal that analytical bias correction outperforms numerical bias corrections obtained from bootstrapping schemes.

Covariance matrix formula for Birnbaum-Saunders regression models

The Birnbaum-Saunders regression model is commonly used in reliability studies. We derive a simple matrix formula for second-order covariances of maximum-likelihood estimators in this class of models. The formula is quite suitable for computer implementation, since it involves only simple operations on matrices and vectors. Some simulation results show that the second-order covariances can be quite pronounced in small to moderate sample sizes. We also present empirical applications.

Influence diagnostics in Birnbaum-Saunders nonlinear regression models

We consider the issue of assessing influence of observations in the class of Birnbaum-Saunders nonlinear regression models, which is useful in lifetime data analysis. Our results generalize those in Galea et al. [8] which are confined to Birnbaum-Saunders linear regression models. Some influence methods, such as the local influence, total local influence of an individual and generalized leverage are discussed. Additionally, the normal curvatures for studying local influence are derived under some perturbation schemes. We also give an application to a real fatigue data set.

Asymptotic skewness in Birnbaum-Saunders nonlinear regression models

The family of distributions proposed by Birnbaum and Saunders (1969) can be used to model lifetime data and it is widely applicable to model failure times of fatiguing materials. We give a simple matrix formula of order n(-1/2), where n is the sample size, for the skewness of the distributions of the maximum likelihood estimates of the parameters in Birnbaum-Saunders nonlinear regression models, recently introduced by Lemonte and Cordeiro (2009). The formula is quite suitable for computer implementation, since it involves only simple operations on matrices and vectors, in order to obtain closed-form skewness in a wide range of nonlinear regression models. Empirical and real applications are analyzed and discussed. (C) 2010 Elsevier B.V. All rights reserved.

Discontinuous Galerkin approximation of two-phase flows in heterogeneous porous media with discontinuous capillary pressures

We design and investigate a sequential discontinuous Galerkin method to approximate two-phase immiscible incompressible flows in heterogeneous porous media with discontinuous capillary pressures. The nonlinear interface conditions are enforced weakly through an adequate design of the penalties on interelement jumps of the pressure and the saturation. An accurate reconstruction of the total velocity is considered in the Raviart-Thomas(-Nedelec) finite element spaces, together with diffusivity-dependent weighted averages to cope with degeneracies in the saturation equation and with media heterogeneities. The proposed method is assessed on one-dimensional test cases exhibiting rough solutions, degeneracies, and capillary barriers. Stable and accurate solutions are obtained without limiters. (C) 2010 Elsevier B.V. All rights reserved.

Some restriction tests in a new class of regression models for proportions

The main purpose of this work is to study the behaviour of Skovgaard`s [Skovgaard, I.M., 2001. Likelihood asymptotics. Scandinavian journal of Statistics 28, 3-32] adjusted likelihood ratio statistic in testing simple hypothesis in a new class of regression models proposed here. The proposed class of regression models considers Dirichlet distributed observations, and the parameters that index the Dirichlet distributions are related to covariates and unknown regression coefficients. This class is useful for modelling data consisting of multivariate positive observations summing to one and generalizes the beta regression model described in Vasconcellos and Cribari-Neto [Vasconcellos, K.L.P., Cribari-Neto, F., 2005. Improved maximum likelihood estimation in a new class of beta regression models. Brazilian journal of Probability and Statistics 19,13-31]. We show that, for our model, Skovgaard`s adjusted likelihood ratio statistics have a simple compact form that can be easily implemented in standard statistical software. The adjusted statistic is approximately chi-squared distributed with a high degree of accuracy. Some numerical simulations show that the modified test is more reliable in finite samples than the usual likelihood ratio procedure. An empirical application is also presented and discussed. (C) 2009 Elsevier B.V. All rights reserved.

Birnbaum-Saunders nonlinear regression models

We introduce, for the first time, a new class of Birnbaum-Saunders nonlinear regression models potentially useful in lifetime data analysis. The class generalizes the regression model described by Rieck and Nedelman [Rieck, J.R., Nedelman, J.R., 1991. A log-linear model for the Birnbaum-Saunders distribution. Technometrics 33, 51-60]. We discuss maximum-likelihood estimation for the parameters of the model, and derive closed-form expressions for the second-order biases of these estimates. Our formulae are easily computed as ordinary linear regressions and are then used to define bias corrected maximum-likelihood estimates. Some simulation results show that the bias correction scheme yields nearly unbiased estimates without increasing the mean squared errors. Two empirical applications are analysed and discussed. Crown Copyright (C) 2009 Published by Elsevier B.V. All rights reserved.

Bias correction in a multivariate normal regression model with general parameterization

This paper derives the second-order biases Of maximum likelihood estimates from a multivariate normal model where the mean vector and the covariance matrix have parameters in common. We show that the second order bias can always be obtained by means of ordinary weighted least-squares regressions. We conduct simulation studies which indicate that the bias correction scheme yields nearly unbiased estimators. (C) 2009 Elsevier B.V. All rights reserved.

Reactions of toluquinone - cyclopentadiene Diels -Alder epoxide adducts with nucleophiles under heterogeneous conditions

Toluquinone-cyclopentadiene Diels-Alder epoxide adducts react with sulfur and oxygen nucleophiles under heterogeneous conditions, leading to products resulting from the epoxide ring opening and from skeletal rearrangement, respectively. Pyrolysis of the sulfanyl adducts gave the new 3-sulfanyltoluquinones (1).

Heterogeneous photocatalytic degradation of acid dyes in aqueous TiO2 suspensions: Kinetics and toxicity

This work assesses the photocatalytic (TiO2/UV) degradation of a simulated acid dye bath (Yellow 3, Red 51, Blue 74, and auxiliary chemicals). Color and phytotoxicity removal were monitored by spectrophotometry and lettuce (Lactuca sativa) seeds as the test organism, respectively. Mineralization was determined by DOC analyses. Photocatalytic, photolytic, and adsorption experiments were performed, showing that adsorption was negligible. After 240 minutes of irradiation, it was achieved 96% and 78% of color removal with photocatalysis and photolysis, respectively. 37% of mineralization occurred with photocatalysis only. The dye bath was rendered completely non-toxic after 60 minutes of photocatalytic treatment; the same result was only achieved with photolysis after 90 minutes. A kinetic model composed of two first-order in series reactions was used. The first photocatalytic decolorization rate constant was k(1) = 0.062 min(-1) and the second k(2) = 0.0043 min(-1), approximately two times greater than the photolytic ones.

Heterogeneous photocatalytic degradation of reactive dyes in aqueous TiO(2) suspensions: Decolorization kinetics

This work assesses the photocatalytic (TiO(2)/UV) degradation of a simulated reactive dye bath (Black 5, Red 239, Yellow 17, and auxiliary chemicals). Color removal was monitored by spectrophotometry. Mineralization was determined by DOC analyses. Photocatalytic, photolytic, and adsorption experiments were performed, showing that adsorption was negligible. After 30 min of irradiation, it was achieved 97% and 40% of color removal with photocatalysis and photolysis, respectively. No mineralization occurred within 30 min. A kinetic model composed of two, first-order in-series reactions was used. The first photocatalytic decolorization rate constant was k(1) = 2.6 min(-1) and the second k(2) = 0.011 min(-1). The fast decolorization of Reactive Black 5 dye is an indication that the number of azo and vinylsulfone groups in the dye molecule maybe a determining factor for the increased photolytic and photocatalytic color removal and degradation rates. (C) 2008 Elsevier B.V. All rights reserved.