Improved maximum likelihood estimators in a heteroskedastic errors-in-variables model

This paper develops a bias correction scheme for a multivariate heteroskedastic errors-in-variables model. The applicability of this model is justified in areas such as astrophysics, epidemiology and analytical chemistry, where the variables are subject to measurement errors and the variances vary with the observations. We conduct Monte Carlo simulations to investigate the performance of the corrected estimators. The numerical results show that the bias correction scheme yields nearly unbiased estimates. We also give an application to a real data set.

A multivariate ultrastructural errors-in-variables model with equation error

This paper deals with asymptotic results on a multivariate ultrastructural errors-in-variables regression model with equation errors Sufficient conditions for attaining consistent estimators for model parameters are presented Asymptotic distributions for the line regression estimators are derived Applications to the elliptical class of distributions with two error assumptions are presented The model generalizes previous results aimed at univariate scenarios (C) 2010 Elsevier Inc All rights reserved

Heteroscedastic controlled calibration model applied to analytical chemistry

In chemical analyses performed by laboratories, one faces the problem of determining the concentration of a chemical element in a sample. In practice, one deals with the problem using the so-called linear calibration model, which considers that the errors associated with the independent variables are negligible compared with the former variable. In this work, a new linear calibration model is proposed assuming that the independent variables are subject to heteroscedastic measurement errors. A simulation study is carried out in order to verify some properties of the estimators derived for the new model and it is also considered the usual calibration model to compare it with the new approach. Three applications are considered to verify the performance of the new approach. Copyright (C) 2010 John Wiley & Sons, Ltd.

Bayesian Analysis for Nonlinear Regression Model Under Skewed Errors, with Application in Growth Curves

We have considered a Bayesian approach for the nonlinear regression model by replacing the normal distribution on the error term by some skewed distributions, which account for both skewness and heavy tails or skewness alone. The type of data considered in this paper concerns repeated measurements taken in time on a set of individuals. Such multiple observations on the same individual generally produce serially correlated outcomes. Thus, additionally, our model does allow for a correlation between observations made from the same individual. We have illustrated the procedure using a data set to study the growth curves of a clinic measurement of a group of pregnant women from an obstetrics clinic in Santiago, Chile. Parameter estimation and prediction were carried out using appropriate posterior simulation schemes based in Markov Chain Monte Carlo methods. Besides the deviance information criterion (DIC) and the conditional predictive ordinate (CPO), we suggest the use of proper scoring rules based on the posterior predictive distribution for comparing models. For our data set, all these criteria chose the skew-t model as the best model for the errors. These DIC and CPO criteria are also validated, for the model proposed here, through a simulation study. As a conclusion of this study, the DIC criterion is not trustful for this kind of complex model.

Influence diagnostics for linear models with first-order autoregressive elliptical errors

We introduce in this paper the class of linear models with first-order autoregressive elliptical errors. The score functions and the Fisher information matrices are derived for the parameters of interest and an iterative process is proposed for the parameter estimation. Some robustness aspects of the maximum likelihood estimates are discussed. The normal curvatures of local influence are also derived for some usual perturbation schemes whereas diagnostic graphics to assess the sensitivity of the maximum likelihood estimates are proposed. The methodology is applied to analyse the daily log excess return on the Microsoft whose empirical distributions appear to have AR(1) and heavy-tailed errors. (C) 2008 Elsevier B.V. All rights reserved.

Hypothesis testing in an errors-in-variables model with heteroscedastic measurement errors

In many epidemiological studies it is common to resort to regression models relating incidence of a disease and its risk factors. The main goal of this paper is to consider inference on such models with error-prone observations and variances of the measurement errors changing across observations. We suppose that the observations follow a bivariate normal distribution and the measurement errors are normally distributed. Aggregate data allow the estimation of the error variances. Maximum likelihood estimates are computed numerically via the EM algorithm. Consistent estimation of the asymptotic variance of the maximum likelihood estimators is also discussed. Test statistics are proposed for testing hypotheses of interest. Further, we implement a simple graphical device that enables an assessment of the model`s goodness of fit. Results of simulations concerning the properties of the test statistics are reported. The approach is illustrated with data from the WHO MONICA Project on cardiovascular disease. Copyright (C) 2008 John Wiley & Sons, Ltd.

Wavelet regression with correlated errors on a piecewise Holder class

This paper generalizes the methodology of Cat and Brown [Cai, T., Brown, L.D., 1998. Wavelet shrinkage for nonequispaced samples. The Annals of Statistics 26, 1783-1799] for wavelet shrinkage for nonequispaced samples, but in the presence of correlated stationary Gaussian errors. If the true function is a member of a piecewise Holder class, it is shown that, even for long memory errors, the rate of convergence of the procedure is almost-minimax relative to the independent and identically distributed errors case. (c) 2008 Elsevier B.V. All rights reserved.

Characterization of O(2) ((1)Delta(g))-Derived Oxidation Products of Tryptophan: A Combination of Tandem Mass Spectrometry Analyses and Isotopic Labeling Studies

The fragmentation mechanisms of singlet oxygen [O(2) ((1)Delta(g))]-derived oxidation products of tryptophan (W) were analyzed using collision-induced dissociation coupled with (18)O-isotopic labeling experiments and accurate mass measurements. The five identified oxidized products, namely two isomeric alcohols (trans and cis WOH), two isomeric hydroperoxides (trans and cis WOOH), and N-formylkynurenine (FMK), were shown to share some common fragment ions and losses of small neutral molecules. Conversely, each oxidation product has its own fragmentation mechanism and intermediates, which were confirmed by (18)O-labeling studies. Isomeric WOH lost mainly H(2)O + CO, while WOOH showed preferential elimination of C(2)H(5)NO(3) by two distinct mechanisms. Differences in the spatial arrangement of the two isomeric WOHs led to differences in the intensities of the fragment ions. The same behavior was also found for trans and cis WOOH. FMK was shown to dissociate by a diverse range of mechanisms, with the loss of ammonia the most favored route. MS/MS analyses, (18)O-labeling, and H(2)(18)O experiments demonstrated the ability of FMK to exchange its oxygen atoms with water. Moreover, this approach also revealed that the carbonyl group has more pronounced oxygen exchange ability compared with the formyl group. The understanding of fragmentation mechanisms involved in O(2) ((1)Delta(g))-mediated oxidation of W provides a useful step toward the structural characterization of oxidized peptides and proteins. (J Am Soc Mass Spectrom 2009, 20, 188-197) (C) 2009 Published by Elsevier Inc. on behalf of American Society for Mass Spectrometry

Trypanosoma cruzi MSH2: Functional analyses on different parasite strains provide evidences for a role on the oxidative stress response

Components of the DNA mismatch repair (MMR) pathway are major players in processes known to generate genetic diversity, such as mutagenesis and DNA recombination. Trypanosoma cruzi, the protozoan parasite that causes Chagas disease has a highly heterogeneous population, composed of a pool of strains with distinct characteristics. Studies with a number of molecular markers identified up to six groups in the T. cruzi population, which showed distinct levels of genetic variability. To investigate the molecular basis for such differences, we analyzed the T. cruzi MSH2 gene, which encodes a key component of MMR, and showed the existence of distinct isoforms of this protein. Here we compared cell survival rates after exposure to genotoxic agents and levels of oxidative stress-induced DNA in different parasite strains. Analyses of msh2 mutants in both T. cruzi and T. brucei were also used to investigate the role of Tcmsh2 in the response to various DNA damaging agents. The results suggest that the distinct MSH2 isoforms have differences in their activity. More importantly, they also indicate that, in addition to its role in MMR, TcMSH2 acts in the parasite response to oxidative stress through a novel mitochondrial function that may be conserved in T. brucei. (C) 2010 Elsevier B.V. All rights reserved.

Fast and reliable analyses of sulphite in fruit juices using a supramolecular amperometric detector encompassing in flow gas diffusion unit

A new compact system encompassing in flow gas diffusion unit and a wall-jet amperometric FIA detector, coated with a supramolecular porphyrin film, was specially designed as an alternative to the time-consuming Monier-Williams method, allowing fast, reproducible and accurate analyses of free sulphite species in fruit juices. In fact, a linear response between 0.64 and 6.4 ppm of sodium sulphite. LOD = 0.043 ppm, relative standard deviation of +/- 1.5% (n = 10) and analytical frequency of 85 analyses/h were obtained utilising optimised conditions. That superior analytical performance allows the precise evaluation of the amount of free sulphite present in foods, providing an important comparison between the standard addition and the standard injection methods. Although the first one is most frequently used, it was strongly influenced by matrix effects because of the unexpected reactivity of sulphite ions with the juice matrixes, leading to its partial consumption soon after addition. In contrast, the last method was not susceptible to matrix effects yielding accurate results, being more reliable for analytical purposes. (C) 2011 Elsevier Ltd. All rights reserved.

SEM, EPR and ToF-SIMS analyses applied to unravel the technology employed for pottery-making by pre-colonial Indian tribes from Pantanal, Brazil

The present work aims at elucidating the technology applied in the fabrication of ceramic objects by the ancient ceramists that inhabited the western border of Pantanal, Mato-Grosso do Sul, with the help of a multidisciplinary approach making use of chemical and physical methods of analysis. The potshards under study show the presence of different types of additives, as determined by scanning electron microscopy (SEM) and time of flight secondary ion mass spectrometry (ToF-SIMS). The dispersion of the additives within the ceramic matrix was also addressed by SEM, which shed light on the mounting technique used by the potters to assemble the ceramic vessels. Moreover, the tensile strength conferred to the pottery by the use of a specific type of additive was evaluated by applying a mechanical test. These results were correlated with the firing temperature of the potshards, determined by means of electron paramagnetic resonance (EPR). (C) 2010 Elsevier Ltd. All rights reserved.