Bayesian nonlinear regression models with scale mixtures of skew-normal distributions: Estimation and case influence diagnostics

The purpose of this paper is to develop a Bayesian analysis for nonlinear regression models under scale mixtures of skew-normal distributions. This novel class of models provides a useful generalization of the symmetrical nonlinear regression models since the error distributions cover both skewness and heavy-tailed distributions such as the skew-t, skew-slash and the skew-contaminated normal distributions. The main advantage of these class of distributions is that they have a nice hierarchical representation that allows the implementation of Markov chain Monte Carlo (MCMC) methods to simulate samples from the joint posterior distribution. In order to examine the robust aspects of this flexible class, against outlying and influential observations, we present a Bayesian case deletion influence diagnostics based on the Kullback-Leibler divergence. Further, some discussions on the model selection criteria are given. The newly developed procedures are illustrated considering two simulations study, and a real data previously analyzed under normal and skew-normal nonlinear regression models. (C) 2010 Elsevier B.V. All rights reserved.

On estimation and influence diagnostics for log-Birnbaum-Saunders Student-t regression models: Full Bayesian analysis

The purpose of this paper is to develop a Bayesian approach for log-Birnbaum-Saunders Student-t regression models under right-censored survival data. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the considered model. In order to attenuate the influence of the outlying observations on the parameter estimates, we present in this paper Birnbaum-Saunders models in which a Student-t distribution is assumed to explain the cumulative damage. Also, some discussions on the model selection to compare the fitted models are given and case deletion influence diagnostics are developed for the joint posterior distribution based on the Kullback-Leibler divergence. The developed procedures are illustrated with a real data set. (C) 2010 Elsevier B.V. All rights reserved.

Influence diagnostics in nonlinear mixed-effects elliptical models

In this work we propose and analyze nonlinear elliptical models for longitudinal data, which represent an alternative to gaussian models in the cases of heavy tails, for instance. The elliptical distributions may help to control the influence of the observations in the parameter estimates by naturally attributing different weights for each case. We consider random effects to introduce the within-group correlation and work with the marginal model without requiring numerical integration. An iterative algorithm to obtain maximum likelihood estimates for the parameters is presented, as well as diagnostic results based on residual distances and local influence [Cook, D., 1986. Assessment of local influence. journal of the Royal Statistical Society - Series B 48 (2), 133-169; Cook D., 1987. Influence assessment. journal of Applied Statistics 14 (2),117-131; Escobar, L.A., Meeker, W.Q., 1992, Assessing influence in regression analysis with censored data, Biometrics 48, 507-528]. As numerical illustration, we apply the obtained results to a kinetics longitudinal data set presented in [Vonesh, E.F., Carter, R.L., 1992. Mixed-effects nonlinear regression for unbalanced repeated measures. Biometrics 48, 1-17], which was analyzed under the assumption of normality. (C) 2009 Elsevier B.V. All rights reserved.

Upgrading a TCABR data analysis and acquisition system for remote participation using Java, XML, RCP and modern client/server communication/authentication

The TCABR data analysis and acquisition system has been upgraded to support a joint research programme using remote participation technologies. The architecture of the new system uses Java language as programming environment. Since application parameters and hardware in a joint experiment are complex with a large variability of components, requirements and specification solutions need to be flexible and modular, independent from operating system and computer architecture. To describe and organize the information on all the components and the connections among them, systems are developed using the extensible Markup Language (XML) technology. The communication between clients and servers uses remote procedure call (RPC) based on the XML (RPC-XML technology). The integration among Java language, XML and RPC-XML technologies allows to develop easily a standard data and communication access layer between users and laboratories using common software libraries and Web application. The libraries allow data retrieval using the same methods for all user laboratories in the joint collaboration, and the Web application allows a simple graphical user interface (GUI) access. The TCABR tokamak team in collaboration with the IPFN (Instituto de Plasmas e Fusao Nuclear, Instituto Superior Tecnico, Universidade Tecnica de Lisboa) is implementing this remote participation technologies. The first version was tested at the Joint Experiment on TCABR (TCABRJE), a Host Laboratory Experiment, organized in cooperation with the IAEA (International Atomic Energy Agency) in the framework of the IAEA Coordinated Research Project (CRP) on ""Joint Research Using Small Tokamaks"". (C) 2010 Elsevier B.V. All rights reserved.

Femtosecond light distribution at skin and liver of rats: analysis for use in optical diagnostics

In this study we investigated the light distribution under femtosecond laser illumination and its correlation with the collected diffuse scattering at the surface of ex-vivo rat skin and liver. The reduced scattering coefficients mu`s for liver and skin due to different scatterers have been determined with Mie-scattering theory for each wavelength (800, 630, and 490 nm). Absorption coefficients mu(a) were determined by diffusion approximation equation in correlation with measured diffused reflectance experimentally for each wavelength (800, 630, and 490 nm). The total attenuation coefficient for each wavelength and type of tissue were determined by linearly fitting the log based normalized intensity. Both tissues are strongly scattering thick tissues. Our results may be relevant when considering the use of femtosecond laser illumination as an optical diagnostic tool. [GRAPHICS] A typical sample of skin exposed to 630 nm laser light (C) 2010 by Astro Ltd. Published exclusively by WILEY-VCH Verlag GmbH & Co. KGaA

Remote Spectroscopy in the Visible Using Fibers on the Optical Internet Network

The work presented here demonstrates the feasibility of using the single-mode fibers of an optical Internet network to deliver visible light between separate laboratories as a way to perform remote spectroscopy in the visible for teaching purposes. The coupling of a broadband light source into the single-mode fiber (SMF) and the characterization of optical losses as a function of the wavelength are discussed. Sample spectra were measured with a portable spectrometer controlled by an acquisition program developed with the LabVIEW software that allows the data to be collected and analyzed.

A geochemical and lead isotopic record from a small pond in a remote equatorial island, Fernando de Noronha, Brazil

A 72 cm long core was collected from Lagoa da Viracao (LV), a small poind in the Fernando de Noronha island, northern Brazil. Sediments from the lower section of the core (20-72 cm depth) contain essentially mineral matter, while in the upper section (0-20 cm depth) mineral matter is mixed with organic matter. Lithogenic conservative elements - Si, Al, Fe, Ti, Co, Cr, Cu, Ba, Ga, Hf, Nb, Ni, Y, V, Zn, Zr and REE - exhibit remarkably constant values throughout the core, with concentrations similar to those of the bedrock. The vertical distribution of soluble elements - Ca, Mg, Na, K, P, Mn and Sr - is also homogeneous, but these elements are systematically depleted in relation to the bedrock. LOI, TOC, Br, Se, Hg and Pb, although showing nearly constant values in the lower section of the core, are significantly enriched in the upper section. The concentration profiles of Br and Se suggest that they may be accounted for by natural processes, related to the slight affinity of these elements for organic matter. On the other hand, the elevated levels of Hg and Pb in recent sediments may be explained by their long-range atmospheric transport and deposition. Furthermore, the isotopic composition of Pb clearly indicates that anthropogenic sources contributed to the Pb burden in the uppermost pond sediments.

Archaeological Mounds in Marajo Island in Northern Brazil: A Geological Perspective Integrating Remote Sensing and Sedimentology

Earthen mounds with archaeological artifacts have been well known in Marajo Island since the 19th century. Their documented dimensions are impressive, e.g., up to 20m high, and with areas large as 90 ha. The mounds, locally known as lesos, impose a significant. relief on the very low-lying landscape of this region, which averages 4 to 6 in above present. sea level. These features have been traditionally interpreted as artificial constructions of the Marajoara culture, designed for defense, cemetery purposes, or escape from flooding. Here, we provide sedimentological and geomorphological data that suggest an alternative origin for these structures that is more consistent with their monumental sizes. Rather than artificial, the Marajoara tesos seem to consist of natural morphological features related to late Pleistocene and Holocene fluvial, and possibly tidal-influenced, paleochannels and paleobars that became abandoned as depositional conditions changed through dine. Although utilized and modified by the Marajoara since at least 2000 years ago, these earthen mounds contain a significant non-anthropogenically modified sedimentary substratum. Therefore, the large Marajoara tesos are not entirely artificial. Ancient, Marajoara cultures took advantage of these natural, preexisting elevated surfaces to base their communities and develop their activities, locally increasing the sizes of these fluvial landforms. This alternative interpretation suggests less cumulative labor investment, in the construction of the mounds and might. have significant implications for reconstructing the organization of the Marajoara culture. (C) 2009 Wiley Periodicals, Inc.

On estimation and influence diagnostics for the Grubbs` model under heavy-tailed distributions

The Grubbs` measurement model is frequently used to compare several measuring devices. It is common to assume that the random terms have a normal distribution. However, such assumption makes the inference vulnerable to outlying observations, whereas scale mixtures of normal distributions have been an interesting alternative to produce robust estimates, keeping the elegancy and simplicity of the maximum likelihood theory. The aim of this paper is to develop an EM-type algorithm for the parameter estimation, and to use the local influence method to assess the robustness aspects of these parameter estimates under some usual perturbation schemes, In order to identify outliers and to criticize the model building we use the local influence procedure in a Study to compare the precision of several thermocouples. (C) 2008 Elsevier B.V. All rights reserved.

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.

Influence Diagnostics for a Skew Extension of the Grubbs Measurement Error Model

Influence diagnostics methods are extended in this article to the Grubbs model when the unknown quantity x (latent variable) follows a skew-normal distribution. Diagnostic measures are derived from the case-deletion approach and the local influence approach under several perturbation schemes. The observed information matrix to the postulated model and Delta matrices to the corresponding perturbed models are derived. Results obtained for one real data set are reported, illustrating the usefulness of the proposed methodology.

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.

Influence diagnostics in beta regression

We consider the issue of assessing influence of observations in the class of beta regression models, which is useful for modelling random variables that assume values in the standard unit interval and are affected by independent variables. We propose a Cook-like distance and also measures of local influence under different perturbation schemes. Applications using real data are presented. (c) 2008 Elsevier B.V.. All rights reserved.

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.

A note on influence diagnostics in nonlinear mixed-effects elliptical models

This paper provides general matrix formulas for computing the score function, the (expected and observed) Fisher information and the A matrices (required for the assessment of local influence) for a quite general model which includes the one proposed by Russo et al. (2009). Additionally, we also present an expression for the generalized leverage on fixed and random effects. The matrix formulation has notational advantages, since despite the complexity of the postulated model, all general formulas are compact, clear and have nice forms. (C) 2010 Elsevier B.V. All rights reserved.