Influence Assessment in an Heteroscedastic Errors-in-Variables Model

The main goal of this article is to consider influence assessment in models with error-prone observations and variances of the measurement errors changing across observations. The techniques enable to identify potential influential elements and also to quantify the effects of perturbations in these elements on some results of interest. The approach is illustrated with data from the WHO MONICA Project on cardiovascular disease.

Influence diagnostics in heteroscedastic and/or autoregressive nonlinear elliptical models for correlated data

In this paper, we propose nonlinear elliptical models for correlated data with heteroscedastic and/or autoregressive structures. Our aim is to extend the models proposed by Russo et al. [22] by considering a more sophisticated scale structure to deal with variations in data dispersion and/or a possible autocorrelation among measurements taken throughout the same experimental unit. Moreover, to avoid the possible influence of outlying observations or to take into account the non-normal symmetric tails of the data, we assume elliptical contours for the joint distribution of random effects and errors, which allows us to attribute different weights to the observations. We propose an iterative algorithm to obtain the maximum-likelihood estimates for the parameters and derive the local influence curvatures for some specific perturbation schemes. The motivation for this work comes from a pharmacokinetic indomethacin data set, which was analysed previously by Bocheng and Xuping [1] under normality.

Influence diagnostics in Gaussian spatial linear models

Spatial linear models have been applied in numerous fields such as agriculture, geoscience and environmental sciences, among many others. Spatial dependence structure modelling, using a geostatistical approach, is an indispensable tool to estimate the parameters that define this structure. However, this estimation may be greatly affected by the presence of atypical observations in the sampled data. The purpose of this paper is to use diagnostic techniques to assess the sensitivity of the maximum-likelihood estimators, covariance functions and linear predictor to small perturbations in the data and/or the spatial linear model assumptions. The methodology is illustrated with two real data sets. The results allowed us to conclude that the presence of atypical values in the sample data have a strong influence on thematic maps, changing the spatial dependence structure.

Influence diagnostics for elliptical semiparametric mixed models

In this paper we extend semiparametric mixed linear models with normal errors to elliptical errors in order to permit distributions with heavier and lighter tails than the normal ones. Penalized likelihood equations are applied to derive the maximum penalized likelihood estimates (MPLEs) which appear to be robust against outlying observations in the sense of the Mahalanobis distance. A reweighed iterative process based on the back-fitting method is proposed for the parameter estimation and the local influence curvatures are derived under some usual perturbation schemes to study the sensitivity of the MPLEs. Two motivating examples preliminarily analyzed under normal errors are reanalyzed considering some appropriate elliptical errors. The local influence approach is used to compare the sensitivity of the model estimates.

Estimation and diagnostics for heteroscedastic nonlinear regression models based on scale mixtures of skew-normal distributions

An extension of some standard likelihood based procedures to heteroscedastic nonlinear regression models under scale mixtures of skew-normal (SMSN) distributions is developed. This novel class of models provides a useful generalization of the heteroscedastic symmetrical nonlinear regression models (Cysneiros et al., 2010), since the random term distributions cover both symmetric as well as asymmetric and heavy-tailed distributions such as skew-t, skew-slash, skew-contaminated normal, among others. A simple EM-type algorithm for iteratively computing maximum likelihood estimates of the parameters is presented and the observed information matrix is derived analytically. In order to examine the performance of the proposed methods, some simulation studies are presented to show the robust aspect of this flexible class against outlying and influential observations and that the maximum likelihood estimates based on the EM-type algorithm do provide good asymptotic properties. Furthermore, local influence measures and the one-step approximations of the estimates in the case-deletion model are obtained. Finally, an illustration of the methodology is given considering a data set previously analyzed under the homoscedastic skew-t nonlinear regression model. (C) 2012 Elsevier B.V. All rights reserved.

THE LOG-BURR XII REGRESSION MODEL FOR GROUPED SURVIVAL DATA

The log-Burr XII regression model for grouped survival data is evaluated in the presence of many ties. The methodology for grouped survival data is based on life tables, where the times are grouped in k intervals, and we fit discrete lifetime regression models to the data. The model parameters are estimated by maximum likelihood and jackknife methods. To detect influential observations in the proposed model, diagnostic measures based on case deletion, so-called global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to these measures, the total local influence and influential estimates are also used. We conduct Monte Carlo simulation studies to assess the finite sample behavior of the maximum likelihood estimators of the proposed model for grouped survival. A real data set is analyzed using a regression model for grouped data.

A log-Birnbaum-Saunders regression model with asymmetric errors

This paper introduces a skewed log-Birnbaum-Saunders regression model based on the skewed sinh-normal distribution proposed by Leiva et al. [A skewed sinh-normal distribution and its properties and application to air pollution, Comm. Statist. Theory Methods 39 (2010), pp. 426-443]. Some influence methods, such as the local influence and generalized leverage, are presented. Additionally, we derived the normal curvatures of local influence under some perturbation schemes. An empirical application to a real data set is presented in order to illustrate the usefulness of the proposed model.

The negative binomial-beta Weibull regression model to predict the cure of prostate cancer

In this article, for the first time, we propose the negative binomial-beta Weibull (BW) regression model for studying the recurrence of prostate cancer and to predict the cure fraction for patients with clinically localized prostate cancer treated by open radical prostatectomy. The cure model considers that a fraction of the survivors are cured of the disease. The survival function for the population of patients can be modeled by a cure parametric model using the BW distribution. We derive an explicit expansion for the moments of the recurrence time distribution for the uncured individuals. The proposed distribution can be used to model survival data when the hazard rate function is increasing, decreasing, unimodal and bathtub shaped. Another advantage is that the proposed model includes as special sub-models some of the well-known cure rate models discussed in the literature. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes. We analyze a real data set for localized prostate cancer patients after open radical prostatectomy.

COMPARISON MEASURES OF MAPS GENERATED BY GEOSTATISTICAL METHODS

This study uses several measures derived from the error matrix for comparing two thematic maps generated with the same sample set. The reference map was generated with all the sample elements and the map set as the model was generated without the two points detected as influential by the analysis of local influence diagnostics. The data analyzed refer to the wheat productivity in an agricultural area of 13.55 ha considering a sampling grid of 50 x 50 m comprising 50 georeferenced sample elements. The comparison measures derived from the error matrix indicated that despite some similarity on the maps, they are different. The difference between the estimated production by the reference map and the actual production was of 350 kilograms. The same difference calculated with the mode map was of 50 kilograms, indicating that the study of influential points is of fundamental importance to obtain a more reliable estimative and use of measures obtained from the error matrix is a good option to make comparisons between thematic maps.

A log-linear regression model for the beta-Birnbaum-Saunders distribution with censored data

The beta-Birnbaum-Saunders (Cordeiro and Lemonte, 2011) and Birnbaum-Saunders (Birnbaum and Saunders, 1969a) distributions have been used quite effectively to model failure times for materials subject to fatigue and lifetime data. We define the log-beta-Birnbaum-Saunders distribution by the logarithm of the beta-Birnbaum-Saunders distribution. Explicit expressions for its generating function and moments are derived. We propose a new log-beta-Birnbaum-Saunders regression model that can be applied to censored data and be used more effectively in survival analysis. We obtain the maximum likelihood estimates of the model parameters for censored data and investigate influence diagnostics. The new location-scale regression model is modified for the possibility that long-term survivors may be presented in the data. Its usefulness is illustrated by means of two real data sets. (C) 2011 Elsevier B.V. All rights reserved.

Robust statistical modeling using the Birnbaum-Saunders-t distribution applied to insurance

In this paper, we carry out robust modeling and influence diagnostics in Birnbaum-Saunders (BS) regression models. Specifically, we present some aspects related to BS and log-BS distributions and their generalizations from the Student-t distribution, and develop BS-t regression models, including maximum likelihood estimation based on the EM algorithm and diagnostic tools. In addition, we apply the obtained results to real data from insurance, which shows the uses of the proposed model. Copyright (c) 2011 John Wiley & Sons, Ltd.

Comparison measures of maps generated by geostatistical methods

This study uses several measures derived from the error matrix for comparing two thematic maps generated with the same sample set. The reference map was generated with all the sample elements and the map set as the model was generated without the two points detected as influential by the analysis of local influence diagnostics. The data analyzed refer to the wheat productivity in an agricultural area of 13.55 ha considering a sampling grid of 50 x 50 m comprising 50 georeferenced sample elements. The comparison measures derived from the error matrix indicated that despite some similarity on the maps, they are different. The difference between the estimated production by the reference map and the actual production was of 350 kilograms. The same difference calculated with the mode map was of 50 kilograms, indicating that the study of influential points is of fundamental importance to obtain a more reliable estimative and use of measures obtained from the error matrix is a good option to make comparisons between thematic maps.

The influence of large-scale circulation, transient and local processes on the seasonal circulation of the Eastern Brazilian Shelf, 13 degrees S

The circulation at the Eastern Brazilian Shelf (EBS), near 13 degrees S, is discussed in terms of the currents and hydrography, associating large-scale circulation, transient and local processes to establish a regional picture of the EBS circulation. The results show that the circulation within the continental shelf and slope region is strongly affected by the seasonal changes in the wind field and mesa/large-scale circulation. Transient processes associated to the passage of Cold Front systems or meso-scale activity and the presence of a local canyon add more complexity to the system. During the austral spring and summer seasons, the prevailing upwelling favorable winds blowing from E-NE were responsible for driving southwestward shelf currents. The interaction with the Western Boundary Current (the Brazil Current), especially during summer, was significant and a considerable vertical shear in the velocity field was observed at the outer shelf. The passage of a Cold Front system during the springtime caused a complete reversal of the mean flow and contributed to the deepening of the Mixed Layer Depth (MLD). In addition, the presence of Salvador Canyon, subject to an upwelling favorable boundary current, enhanced the upwelling system, when compared to the upwelling observed at the adjacent shelf. During the austral autumn and winter seasons the prevailing downwelling favorable winds blowing from the SE acted to total reverse the shelf circulation, resulting in a northeastward flow. The passage of a strong Cold Front, during the autumn season, contributed not only to the strengthening of the flow but also to the deepening of the MLD. The presence of the Salvador Canyon, when subject to a downwelling favorable boundary current, caused an intensification of the downwelling process. Interestingly, the alongshore velocity at the shelf region adjacent to the head of the canyon was less affected when compared to the upwelling situation.

Influence of normal and radial contributions of local current density on local electrochemical impedance spectroscopy

A new tri-electrode probe is presented and applied to local electrochemical impedance spectroscopy (LEIS) measurements. As opposed to two-probe systems, the three-probe one allows measurement not only of normal, but also of radial contributions of local current densities to the local impedance values. The results concerning the cases of the blocking electrode and the electrode with faradaic reaction are discussed from the theoretical point of view for a disk electrode. Numerical simulations and experimental results are compared for the case of the ferri/ferrocyanide electrode reaction at the Pt working electrode disk. At the centre of the disk, the impedance taking into account both normal and radial contributions was in good agreement with the local impedance measured in terms of only the normal contribution. At the periphery of the electrode, the impedance taking into account both normal and radial contributions differed significantly from the local impedance measured in terms of only the normal contribution. The radial impedance results at the periphery of the electrode are in good agreement with the usual explanation that the associated larger current density is attributed to the geometry of the electrode, which exhibits a greater accessibility at the electrode edge. (C) 2011 Elsevier Ltd. All rights reserved.

Macroalgal composition and its association with local hydrodynamics in the Laje de Santos Marine State Park, southwestern Atlantic, São Paulo, Brazil

The Laje de Santos Marine State Park (LSMSP), located in southeastern Brazil, is the only marine park in Sao Paulo State. This conservation unit has been established as a protected area of high biological diversity. Despite its importance for the conservation of the marine biota, little is known about the park's seaweed flora. The objectives of this study were as follows: to furnish increased knowledge of the composition of the macroalgae in the Park area; to relate the area's macroalgal composition to the presence of an important water mass in the region, the South Atlantic Central Water (SACW); and to investigate the possible influence of the Port of Santos on the composition of the macroalgae of the LSMSP. This study registered 31 new records for the LSMSP, 11 for Sao Paulo State, four for Brazil, one for the western Atlantic and one for the South Atlantic Ocean, in addition to the possible occurrence of one new species of Osmundea (Rhodomelaceae) and one new genus belonging to Ceramiaceae. The taxonomic composition of the macroalgae had a direct correlation with the arrival of the SACW in the summer-fall season. The SACW generated a strong thermocline and increased the supply of nutrients in the water column. Hydrodynamic and dispersion modeling analyses suggested that the Port of Santos influenced the composition of the LSMSP phycoflora.