Inference From Aging Information

For many learning tasks the duration of the data collection can be greater than the time scale for changes of the underlying data distribution. The question we ask is how to include the information that data are aging. Ad hoc methods to achieve this include the use of validity windows that prevent the learning machine from making inferences based on old data. This introduces the problem of how to define the size of validity windows. In this brief, a new adaptive Bayesian inspired algorithm is presented for learning drifting concepts. It uses the analogy of validity windows in an adaptive Bayesian way to incorporate changes in the data distribution over time. We apply a theoretical approach based on information geometry to the classification problem and measure its performance in simulations. The uncertainty about the appropriate size of the memory windows is dealt with in a Bayesian manner by integrating over the distribution of the adaptive window size. Thus, the posterior distribution of the weights may develop algebraic tails. The learning algorithm results from tracking the mean and variance of the posterior distribution of the weights. It was found that the algebraic tails of this posterior distribution give the learning algorithm the ability to cope with an evolving environment by permitting the escape from local traps.

Improved likelihood inference for the shape parameter in Weibull regression

We obtain adjustments to the profile likelihood function in Weibull regression models with and without censoring. Specifically, we consider two different modified profile likelihoods: (i) the one proposed by Cox and Reid [Cox, D.R. and Reid, N., 1987, Parameter orthogonality and approximate conditional inference. Journal of the Royal Statistical Society B, 49, 1-39.], and (ii) an approximation to the one proposed by Barndorff-Nielsen [Barndorff-Nielsen, O.E., 1983, On a formula for the distribution of the maximum likelihood estimator. Biometrika, 70, 343-365.], the approximation having been obtained using the results by Fraser and Reid [Fraser, D.A.S. and Reid, N., 1995, Ancillaries and third-order significance. Utilitas Mathematica, 47, 33-53.] and by Fraser et al. [Fraser, D.A.S., Reid, N. and Wu, J., 1999, A simple formula for tail probabilities for frequentist and Bayesian inference. Biometrika, 86, 655-661.]. We focus on point estimation and likelihood ratio tests on the shape parameter in the class of Weibull regression models. We derive some distributional properties of the different maximum likelihood estimators and likelihood ratio tests. The numerical evidence presented in the paper favors the approximation to Barndorff-Nielsen`s adjustment.

Inference and local influence assessment in skew-normal null intercept measurement error model

In this article, we discuss inferential aspects of the measurement error regression models with null intercepts when the unknown quantity x (latent variable) follows a skew normal distribution. We examine first the maximum-likelihood approach to estimation via the EM algorithm by exploring statistical properties of the model considered. Then, the marginal likelihood, the score function and the observed information matrix of the observed quantities are presented allowing direct inference implementation. In order to discuss some diagnostics techniques in this type of models, we derive the appropriate matrices to assessing the local influence on the parameter estimates under different perturbation schemes. The results and methods developed in this paper are illustrated considering part of a real data set used by Hadgu and Koch [1999, Application of generalized estimating equations to a dental randomized clinical trial. Journal of Biopharmaceutical Statistics, 9, 161-178].

Epsilon Birnbaum-Saunders distribution family: properties and inference

In this paper we introduce a new extension for the Birnbaum-Saunder distribution based on the family of the epsilon-skew-symmetric distributions studied in Arellano-Valle et al. (J Stat Plan Inference 128(2):427-443, 2005). The extension allows generating Birnbaun-Saunders type distributions able to deal with extreme or outlying observations (Dupuis and Mills, IEEE Trans Reliab 47:88-95, 1998). Basic properties such as moments and Fisher information matrix are also studied. Results of a real data application are reported illustrating good fitting properties of the proposed model.

Improved likelihood inference in beta regression

We consider the issue of performing accurate small-sample likelihood-based inference in beta regression models, which are useful for modelling continuous proportions that are affected by independent variables. We derive small-sample adjustments to the likelihood ratio statistic in this class of models. The adjusted statistics can be easily implemented from standard statistical software. We present Monte Carlo simulations showing that inference based on the adjusted statistics we propose is much more reliable than that based on the usual likelihood ratio statistic. A real data example is presented.

Bayesian inference for a skew-normal IRT model under the centred parameterization

Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is interest in studying latent variables. These latent variables are directly considered in the Item Response Models (IRM) and they are usually called latent traits. A usual assumption for parameter estimation of the IRM, considering one group of examinees, is to assume that the latent traits are random variables which follow a standard normal distribution. However, many works suggest that this assumption does not apply in many cases. Furthermore, when this assumption does not hold, the parameter estimates tend to be biased and misleading inference can be obtained. Therefore, it is important to model the distribution of the latent traits properly. In this paper we present an alternative latent traits modeling based on the so-called skew-normal distribution; see Genton (2004). We used the centred parameterization, which was proposed by Azzalini (1985). This approach ensures the model identifiability as pointed out by Azevedo et al. (2009b). Also, a Metropolis Hastings within Gibbs sampling (MHWGS) algorithm was built for parameter estimation by using an augmented data approach. A simulation study was performed in order to assess the parameter recovery in the proposed model and the estimation method, and the effect of the asymmetry level of the latent traits distribution on the parameter estimation. Also, a comparison of our approach with other estimation methods (which consider the assumption of symmetric normality for the latent traits distribution) was considered. The results indicated that our proposed algorithm recovers properly all parameters. Specifically, the greater the asymmetry level, the better the performance of our approach compared with other approaches, mainly in the presence of small sample sizes (number of examinees). Furthermore, we analyzed a real data set which presents indication of asymmetry concerning the latent traits distribution. The results obtained by using our approach confirmed the presence of strong negative asymmetry of the latent traits distribution. (C) 2010 Elsevier B.V. All rights reserved.

Inference for a skew extension of the Grubbs model

In this paper, we discuss inferential aspects for the Grubbs model when the unknown quantity x (latent response) follows a skew-normal distribution, extending early results given in Arellano-Valle et al. (J Multivar Anal 96:265-281, 2005b). Maximum likelihood parameter estimates are computed via the EM-algorithm. Wald and likelihood ratio type statistics are used for hypothesis testing and we explain the apparent failure of the Wald statistics in detecting skewness via the profile likelihood function. The results and methods developed in this paper are illustrated with a numerical example.

Improved likelihood inference in Birnbaum-Saunders regressions

The Birnbaum-Saunders regression model is commonly used in reliability studies. We address the issue of performing inference in this class of models when the number of observations is small. Our simulation results suggest that the likelihood ratio test tends to be liberal when the sample size is small. We obtain a correction factor which reduces the size distortion of the test. Also, we consider a parametric bootstrap scheme to obtain improved critical values and improved p-values for the likelihood ratio test. The numerical results show that the modified tests are more reliable in finite samples than the usual likelihood ratio test. We also present an empirical application. (C) 2009 Elsevier B.V. All rights reserved.

Properties and Inference on the Skew-Curved-Symmetric Family of Distributions

In this article, we study some results related to a specific class of distributions, called skew-curved-symmetric family of distributions that depends on a parameter controlling the skewness and kurtosis at the same time. Special elements of this family which are studied include symmetric and well-known asymmetric distributions. General results are given for the score function and the observed information matrix. It is shown that the observed information matrix is always singular for some special cases. We illustrate the flexibility of this class of distributions with an application to a real dataset on characteristics of Australian athletes.

Improved testing inference in mixed linear models

Mixed linear models are commonly used in repeated measures studies. They account for the dependence amongst observations obtained from the same experimental unit. Often, the number of observations is small, and it is thus important to use inference strategies that incorporate small sample corrections. In this paper, we develop modified versions of the likelihood ratio test for fixed effects inference in mixed linear models. In particular, we derive a Bartlett correction to such a test, and also to a test obtained from a modified profile likelihood function. Our results generalize those in [Zucker, D.M., Lieberman, O., Manor, O., 2000. Improved small sample inference in the mixed linear model: Bartlett correction and adjusted likelihood. Journal of the Royal Statistical Society B, 62,827-838] by allowing the parameter of interest to be vector-valued. Additionally, our Bartlett corrections allow for random effects nonlinear covariance matrix structure. We report simulation results which show that the proposed tests display superior finite sample behavior relative to the standard likelihood ratio test. An application is also presented and discussed. (C) 2008 Elsevier B.V. All rights reserved.

Ultrasensitive Simultaneous Quantification of 1,N(2)-Etheno-2 `-deoxyguanosine and 1,N(2-)Propano-2 `-deoxyguanosine in DNA by an Online Liquid Chromatography-Electrospray Tandem Mass Spectrometry Assay

Exocyclic DNA adducts produced by exogenous and endogenous compounds are emerging as potential tools to study a variety of human diseases and air pollution exposure. A highly sensitive method involving online reverse-phase high performance liquid chromatography with electrospray tandem mass spectrometry detection in the multiple reaction monitoring mode and employing stable isotope-labeled internal standards was developed for the simultaneous quantification of 1,N(2)-etheno-2`-deoxyguanosine (1,N(2)-epsilon dGuo) and 1,N(2)-propano-2`-deoxyguanosine (1,N(2)-propanodGuo) in DNA. This methodology permits direct online quantification of 2`-deoxyguanosine and ca. 500 amol of adducts in 100 mu g of hydrolyzed DNA M the same analysis. Using the newly developed technique, accurate determinations of 1,N(2)-etheno-2`-deoxyguanosine and 1,N2-propano-2`-deoxyguanosine levels in DNA extracts of human cultured cells (4.01 +/- 0.32 1,N(2)-epsilon dGuo/10(8) dGuo and 3.43 +/- 0.33 1,N(2)-propanodGuo/10(8) dGuo) and rat tissue (liver, 2.47 +/- 0.61 1,N(2)-epsilon dGuo/10(8) dGuo and 4.61 +/- 0.69 1,N(2)-propanodGuo/108 dGuo; brain, 2.96 +/- 1.43,N(2)-epsilon dGuo/10(8) dGuo and 5.66 +/- 3.70 1,N(2)-propanoclGuo/10(8) dGuo; and lung, 0,87 +/- 0.34 1,N(2)-edGuo/ 10(8) dGuo and 2.25 +/- 1.72 1,N(2)-propanodGuo/10(8) dGuo) were performed. The method described herein can be used to study the biological significance of exocyclic DNA adducts through the quantification of different adducts in humans and experimental an with pathological conditions and after air pollution exposure.

Simultaneous determination of chromium and manganese in alumina by slurry sampling graphite furnace atomic absorption spectrometry using NbC and NaF as modifiers

This paper reports a method for the direct and simultaneous determination of Cr and Mn in alumina by slurry sampling graphite furnace atomic absorption spectrometry (SiS-SIMAAS) using niobium carbide (NbC) as a graphite platform modifier and sodium fluoride (NaF) as a matrix modifier. 350 mu g of Nb were thermally deposited on the platform surface allowing the formation of NbC (mp 3500 degrees C) to minimize the reaction between aluminium and carbon of the pyrolytic platform, improving the graphite tube lifetime up to 150 heating cycles. A solution of 0.2 mol L(-1) NaF was used as matrix modifier for alumina dissolution as cryolite-based melt, allowing volatilization during pyrolysis step. Masses (c.a. 50 mg) of sample were suspended in 30 ml of 2.0% (v/v) of HNO(3). Slurry was manually homogenized before sampling. Aliquots of 20 mu l of analytical solutions and slurry samples were co-injected into the graphite tube with 20 mu l of the matrix modifier. In the best conditions of the heating program, pyrolysis and atomization temperatures were 1300 degrees C and 2400 degrees C, respectively. A step of 1000 degrees C was optimized allowing the alumina dissolution to form cryolite. The accuracy of the proposed method has been evaluated by the analysis of standard reference materials. The found concentrations presented no statistical differences compared to the certified values at 95% of the confidence level. Limits of detection were 66 ng g(-1) for Cr and 102 ng g(-1) for Mn and the characteristic masses were 10 and 13 pg for Cr and Mn, respectively.

Multivariant optimization, validation, and application of capillary electrophoresis for simultaneous determination of polyphenols and phenolic acids in Brazilian wines

A method for the simultaneous determination of the stilbene resveratrol, four phenolic acids (syringic, coumaric, caffeic, and gallic acids), and five flavonoids (catechin, rutin, kaempferol, myricetin, and quercetin) in wine by CE was developed and validated. The CE electrolyte composition and instrumental conditions were optimized using 2(7-3) factorial design and response surface analysis, showing sodium tetraborate, MeOH, and their interaction as the most influential variables. The optimal electrophoretic conditions, minimizing the chromatographic resolution statistic values, consisted of 17 mmol/L sodium tetraborate with 20% methanol as electrolyte, constant voltage of 25 kV, hydrodynamic injection at 50 mbar for 3 s, and temperature of 25 degrees C. The R(2) values for linearity varied from 0.994 to 0.999; LOD and LOQ were 0.1 to 0.3 mg/L and 0.4 to 0.8 mg/L, respectively. The RSDs for migration time and peak area obtained from ten consecutive injections were less than 2% and recoveries varied from 97 to 102%. The method was applied to 23 samples of inexpensive Brazilian wines, showing wide compositional variation.

Simultaneous voltammetric detection of ascorbic acid, dopamine and uric acid using a pyrolytic graphite electrode modified into dopamine solution

Pyrolytic graphite electrodes (PGE) were modified into dopamine solutions using phosphate buffer solutions, pH 10 and 6.5, as supporting electrolyte. The modification process involved a previous anodization of the working electrode at +1. 5 V into 0. 1 mol-L-1 NaOH followed by other anodization step, in the same experimental conditions, into dopamine (DA) solutions. pH of the supporting electrolyte performed an important role in the production of a superficial melanin polymeric film, which permitted the simultaneous detection of ascorbic acid (AA), (DA) and uric acid (UA), Delta EAA-DA = 222 mV-, Delta EAA-UA = 360 mV and Delta EDA-UA=138mV, avoiding the superficial poisoning effects. The calculated detection limits were: 1.4 x 10(-6) mol L-1 for uric acid, 1.3x10-(5) molL(-1) for ascorbic acid and 1.1 X 10(-7) mol L-1 for dopamine, with sensitivities of (7.7 +/- 0.5), (0.061 +/- 0.001) and (9.5 +/- 0.05)A mol(-1) cm(-2), respectively, with no mutual interference. Uric acid was determined in urine, blood and serum human samples after dilution in phosphate buffer and no additional sample pre-treatment was necessary. The concentration of uric acid in urine was higher than the values found in blood and serum and the recovery tests (92-102%) indicated that no matrix effects were observed. (C) 2008 Elsevier B.V. All rights reserved.

Evaluation of a carbon paste electrode modified with organofunctionalised SBA-15 nanostructured silica in the simultaneous determination of divalent lead, copper and mercury ions

The performance of a carbon paste electrode (CPE) modified with SBA-15 nanostructured silica organofunctionalised with 2-benzothiazolethiol in the simultaneous determination of Pb(II), Cu(II) and Hg(II) ions in natural water and sugar cane spirit (cachaca) is described. Pb(II), Cu(II) and Hg(II) were pre-concentrated on the surface of the modified electrode by complexing with 2-benzothiazolethiol and reduced at a negative potential (-0.80 V). Then the reduced products were oxidised by DPASV procedure. The fact that three stripping peaks appeared on the voltammograms at the potentials of -0.48 V (Pb2+), -0.03 V (Cu2+) and +0.36 V (Hg2+) in relation to the SCE, demonstrates the possibility of simultaneous determination of Pb2+, Cu2+ and Hg2+. The best results were obtained under the following optimised conditions: 100 mV pulse amplitude, 3 min accumulation time, 25 mV s(-1) scan rate in phosphate solution pH 3.0. Using such parameters, calibration graphs were linear in the concentration ranges of 3.00-70.0 x 10(-7) mol L-1 (Pb2+), 8.00-100.0 X 10(-7) mol L-1 (Cu2+) and 2.00-10.0 x 10(-6) mol L-1 (Hg2+). Detection limits of 4.0 x 10(-8) mol L-1 (Pb2+), 2.0 x 10(-7) mol L-1 (Cu2+) and 4.0 x 10(-7) mol L-1 (Hg2+) were obtained at the signal noise ratio (SNR) of 3. The results indicate that this electrode is sensitive and effective for simultaneous determination of Pb2+, Cu2+ and Hg2+ in the analysed samples. (C) 2008 Published by Elsevier B.V.