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].

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.

A modified signed likelihood ratio test in elliptical structural models

In this paper we deal with the issue of performing accurate testing inference on a scalar parameter of interest in structural errors-in-variables models. The error terms are allowed to follow a multivariate distribution in the class of the elliptical distributions, which has the multivariate normal distribution as special case. We derive a modified signed likelihood ratio statistic that follows a standard normal distribution with a high degree of accuracy. Our Monte Carlo results show that the modified test is much less size distorted than its unmodified counterpart. An application is presented.

Measurement error models with a general class of error distribution

In general, the normal distribution is assumed for the surrogate of the true covariates in the classical error model. This paper considers a class of distributions, which includes the normal one, for the variables subject to error. An estimation approach yielding consistent estimators is developed and simulation studies reported.

On the skew-normal calibration model

In this article, we present the EM-algorithm for performing maximum likelihood estimation of an asymmetric linear calibration model with the assumption of skew-normally distributed error. A simulation study is conducted for evaluating the performance of the calibration estimator with interpolation and extrapolation situations. As one application in a real data set, we fitted the model studied in a dimensional measurement method used for calculating the testicular volume through a caliper and its calibration by using ultrasonography as the standard method. By applying this methodology, we do not need to transform the variables to have symmetrical errors. Another interesting aspect of the approach is that the developed transformation to make the information matrix nonsingular, when the skewness parameter is near zero, leaves the parameter of interest unchanged. Model fitting is implemented and the best choice between the usual calibration model and the model proposed in this article was evaluated by developing the Akaike information criterion, Schwarz`s Bayesian information criterion and Hannan-Quinn criterion.

A new class of survival regression models with heavy-tailed errors: robustness and diagnostics

Birnbaum-Saunders models have largely been applied in material fatigue studies and reliability analyses to relate the total time until failure with some type of cumulative damage. In many problems related to the medical field, such as chronic cardiac diseases and different types of cancer, a cumulative damage caused by several risk factors might cause some degradation that leads to a fatigue process. In these cases, BS models can be suitable for describing the propagation lifetime. However, since the cumulative damage is assumed to be normally distributed in the BS distribution, the parameter estimates from this model can be sensitive to outlying observations. In order to attenuate this influence, we present in this paper BS models, in which a Student-t distribution is assumed to explain the cumulative damage. In particular, we show that the maximum likelihood estimates of the Student-t log-BS models attribute smaller weights to outlying observations, which produce robust parameter estimates. Also, some inferential results are presented. In addition, based on local influence and deviance component and martingale-type residuals, a diagnostics analysis is derived. Finally, a motivating example from the medical field is analyzed using log-BS regression models. Since the parameter estimates appear to be very sensitive to outlying and influential observations, the Student-t log-BS regression model should attenuate such influences. The model checking methodologies developed in this paper are used to compare the fitted models.

Bayesian density estimation using Skew Student-t-Normal mixtures

We present a Bayesian approach for modeling heterogeneous data and estimate multimodal densities using mixtures of Skew Student-t-Normal distributions [Gomez, H.W., Venegas, O., Bolfarine, H., 2007. Skew-symmetric distributions generated by the distribution function of the normal distribution. Environmetrics 18, 395-407]. A stochastic representation that is useful for implementing a MCMC-type algorithm and results about existence of posterior moments are obtained. Marginal likelihood approximations are obtained, in order to compare mixture models with different number of component densities. Data sets concerning the Gross Domestic Product per capita (Human Development Report) and body mass index (National Health and Nutrition Examination Survey), previously studied in the related literature, are analyzed. (c) 2008 Elsevier B.V. All rights reserved.

Skew-normal linear calibration: a Bayesian perspective

In this paper, we present a Bayesian approach for estimation in the skew-normal calibration model, as well as the conditional posterior distributions which are useful for implementing the Gibbs sampler. Data transformation is thus avoided by using the methodology proposed. Model fitting is implemented by proposing the asymmetric deviance information criterion, ADIC, a modification of the ordinary DIC. We also report an application of the model studied by using a real data set, related to the relationship between the resistance and the elasticity of a sample of concrete beams. Copyright (C) 2008 John Wiley & Sons, Ltd.

Bayesian Analysis for the Generalized Lognormal Distribution Applied to Failure Time Analysis

There are several versions of the lognormal distribution in the statistical literature, one is based in the exponential transformation of generalized normal distribution (GN). This paper presents the Bayesian analysis for the generalized lognormal distribution (logGN) considering independent non-informative Jeffreys distributions for the parameters as well as the procedure for implementing the Gibbs sampler to obtain the posterior distributions of parameters. The results are used to analyze failure time models with right-censored and uncensored data. The proposed method is illustrated using actual failure time data of computers.

The latitude dependent irradiation distribution in Europe and its implication for the design of stationary concentrators

When a stationary solar concentrator is designed, the spatial distribution of the available irradiation is of vital interest. An irradiation distribution based only on solar geometry will look similar at different sites. The only difference is that the distribution of the incident irradiation is shifted to lower solar altitudes when latitude is increased. However, real irradiation distribution will show strong asymmetry at high latitude sites, since the winter irradiation is reduced by absorption and scattering in the atmosphere, and by seasonal changes in the climate. The reduced winter irradiation at high latitudes implies that the available annual radiation is concentrated to a narrower angular interval. This means that the degree of concentration that is possible increases with latitude.In the paper examples of irradiation distribution from different sites in Europe from latitude 38°N to 65°N are shown. The origin of the reduced winter irradiation with increased latitude is discussed, and numerical examples on the performance of different types of stationary concentrators for different latitudes are given.

Brazilian regional development distribution, evidences for socio-economic policy

As to many Latin american countries, the impacts of the recent economic globalization on the Brazilian economy have revealed a diversified tendency in spatial development when regional economic indicators are observed. This is due to the specificities or each region, as regard their sector structure, the availability of human resources and the degree of technological innovation undertaken by local enterprises. From a situation of regional inequalities observed in lhe socio-economic levels of development at the beginning of the eighties the dynamics of the Brazilian regional evolution has presented different speeds and intensities in the several spaees. This paper aims to evaluate the dynamics of Brazilian regional development during the 1985-95 period and the impacts over the working population and regional disparities in order to offer some elements to assist social and economic policy. For this purpose Dispersion Quotients and Dispersion lntensity Coefficients were calculated based on two variables, the Regional Gross Domestic Product anel the Working Population. The results of the analysis confirm the existence of considerable regional disparities and it was observed that thc sector and regional redistribution of the GDP indicate that in a general way, no remarkable changes occurred in the regional development in the period. The results show that although the economic policies did stimulate a global convergence process of the per capita product among regions, those policies did not attenuate economic dynamism concentration to the desired extent.

Productive restructuring: effects on Brazilian regional development distribution

This paper aims to evaluate the dynamics of Brazilian regional development during the 1985-95 period. First, regional inequalities indexes were calculated for the whole country’s economy based on the per capita regional income (Williamson Inequality Index), in order to test the convergence or divergence. After this, the analysis aimed to verify the sector and regional dynamics in a more detailed exam, and for this purpose Dispersion Quotients and Dispersion Intensity Coefficients were calculated based on two variables, the Regional Gross Domestic Product and the Working Population. The results of the analysis confirm the existence of considerable regional disparities and it was verified that the sector and regional redistribution of the GDP indicate that, in a general way, no remarkable changes occurred in the regional productive structures in the period. It is also inferred that the economic policy at that period, in spite of resulting in a global regional convergence process of the per capita product, did not avoid the continuation of the concentration of greater economic dynamism in the most advanced regions, nor did it diminish in any considerable way the difference in the degree of development of the Northeast region.

The finite-sample size of the BDS test for GARCH standardized residuals

This paper uses a multivariate response surface methodology to analyze the size distortion of the BDS test when applied to standardized residuals of rst-order GARCH processes. The results show that the asymptotic standard normal distribution is an unreliable approximation, even in large samples. On the other hand, a simple log-transformation of the squared standardized residuals seems to correct most of the size problems. Nonethe-less, the estimated response surfaces can provide not only a measure of the size distortion, but also more adequate critical values for the BDS test in small samples.

Estudo clínico-laboratorial e histopatológico de cães naturalmente infectados por Leishmania chagasi com diferentes graus de manifestação física

Canine Visceral Leishmania (CVL) is an important zoonotic disease that has a world wide distribution and has a large impact on public health on the American Continent, especially in Brazil, where the nature of endemic diseases in humans affects a large part of the nation. The influence of the prevalence of CVL in the increased rate of human cases in endemic areas and in the unleashing of epidemic outbreaks shows the need for a more profound understanding, that would generate significant advances in the current measures used to control the reservoirs of sickness that are practiced by the Programa Nacional de Vigilância e Controle da Leishmaniose Visceral. The present work describes and compares the clinical-laboratorial and histopathological findings of twenty-three dogs that were naturally infected by Leishmania chagasi, from endemic areas in metropolitan Natal, Rio Grande do Norte, Brazil. These animals, that were selected and given physical and serological exams (IFI and ELISA rK-39), were classified according to the degree of clinical severity and had blood samples drawn (whole blood and serum) for a complete hemogram and a coagulogram to be done as well as biochemical tests for kidney and liver function. The confirmation of infection by L. chagasi was done after the euthanasia of the animals, through the direct demonstration of the parasite in the impression of the spleen and liver crowned with GIEMSA and through a cultivation by means of NNN/Schneider. According to the clinical evaluation, the animals were classified as asymptomatic (7), oligosymptomatic (7) and polysymptomatic (9). Among the animals that were chosen to be autopsied, there were 2 asymptomatic, 3 oligosymptomatic and 3 polysymptomatic, for the purpose of studying their histopathology, having collected fragments of the spleen, liver, kidneys and skin and were fixed in 10% tamponed formol. The comparison between the average parameters of the clinical-laboratory tested animals in the groups was done through the Student t test (a<0.05). The main clinical signals observed were lymphadenomegaly, alopecy, dermatitis, exfoliation, cutaneous ulcers, onicogriphosis and emaciation. The main clinical-laboratorial alterations established, mainly in the polysymptomatic group, were anemia, hyperproteinemia, hyperglobulinemia, alterations in the albumin/globulin ratio and increased ALT activity. Renal alterations were not verified (urea and creatinine levels were normal). Thrombocytopenia was observed in three clinical groups. However, the other indicators of coagulation function (TAP and TTPA) did not have abnormal variations. There were inflammatory infiltrations and leishmania amastigotes in the skin of polysymptomatic dogs, however, they were not found in the skin of asymptomatic animals. Hypertrophy and hyperplasia of the phagocyte mononuclear system, leishmania amastigote parasites were found in the macrophages, extramedullary hematopoiesis and degenerative alterations were detected in the spleen and liver of 8 of the animals submitted to histopathological exams. In accord with these results, it was demonstrated that the expected alterations in the hematological and biochemical parameters in function of their viscerotropic nature of CVL are mainly observed in the more advanced stages of the disease. The absence of inflammatory infiltration and parasite load in the skin suggest that infected animals without symptoms may have an importance irrelevant to the infectiousness of the vector

Spontaneous Interblink Time Distributions in Patients with Graves' Orbitopathy and Normal Subjects

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)