A log-location-scale lifetime distribution with censored data: Regression modeling,residuals, and global influence

In survival analysis applications, the presence of failure rate functions with non monotone shapes is common. Therefore, models that can accommodate such different shapes are needed. In this article, we present a location regression model based on the complementary exponentiated exponential geometric distribution as an alternative to the usual bathtub, increasing, and decreasing failure rates in lifetime data. Assuming censored data, we consider the maximum likelihood inference for analysis, graphical verification for residuals, and test statistics for influential points.     

Estimating the stability of census-based racial/ethnic classifications: the case of Brazil

This study presents a method of estimating the degree to which people change their racial/ethnic identity from one census enumeration to another. The technique is applied to the classification of skin colour in Brazil (white, black, brown, yellow). For the period 1950-80, the findings show a deficit of 38 per cent in the black category and a gain of 34 per cent in the brown category, suggesting that a large proportion of individuals who declared themselves black in 1950 reclassified themselves as brown in 1980. Estimates for 1980-90, adjusted for the effects of international migration, reveal a similar pattern, although the magnitude of colour reclassification may have declined somewhat during the 1980s. Procedures to determine the stability of racial/ethnic identity produce data useful to recent policy initiatives that rely on demographic censuses to measure changes in the status of minority groups in less developed countries.     

A Comparison Between Maximum Likelihood and Bayesian Estimation of Stochastic Frontier Production Models

In this paper, the finite sample properties of the maximum likelihood and Bayesian estimators of the half-normal stochastic frontier production function are analyzed and compared through a Monte Carlo study. The results show that the Bayesian estimator should be used in preference to the maximum likelihood owing to the fact that the mean square error performance is substantially better in the Bayesian framework.     

Comparing the performance of normality tests with ROC analysis and confidence intervals

There are several statistical hypothesis tests available for assessing normality assumptions, which is an a priori requirement for most parametric statistical procedures. The usual method for comparing the performances of normality tests is to use Monte Carlo simulations to obtain point estimates for the corresponding powers. The aim of this work is to improve the assessment of 9 normality hypothesis tests. For that purpose, random samples were drawn from several symmetric and asymmetric nonnormal distributions and Monte Carlo simulations were carried out to compute confidence intervals for the power achieved, for each distribution, by two of the most usual normality tests, Kolmogorov–Smirnov with Lilliefors correction and Shapiro–Wilk. In addition, the specificity was computed for each test, again resorting to Monte Carlo simulations, taking samples from standard normal distributions. The analysis was then additionally extended to the Anderson–Darling, Cramer-Von Mises, Pearson chi-square Shapiro–Francia, Jarque–Bera, D'Agostino and uncorrected Kolmogorov–Smirnov tests by determining confidence intervals for the areas under the receiver operating characteristic curves. Simulations were performed to this end, wherein for each sample from a nonnormal distribution an equal-sized sample was taken from a normal distribution. The Shapiro–Wilk test was seen to have the best global performance overall, though in some circumstances the Shapiro–Francia or the D'Agostino tests offered better results. The differences between the tests were not as clear for smaller sample sizes. Also to be noted, the SW and KS tests performed generally quite poorly in distinguishing between samples drawn from normal distributions and t Student distributions.     

Analytical expressions for the average adjustment interval and mean squared deviation for bounded adjustment schemes

This paper presents analytical expressions for the average adjustment interval and the mean squared deviation from target of the “bounded adjustment” schemes of Box and Luceno (1997a) under the assumption that the disturbances are generated from a double-exponential distribution. The solutions obtained are very close to those computed numerically for normally distributed innovations. This not only demonstrates the robustness of the schemes to the distributional assumptions, but also provides new useful expressions for the average adjustment interval and mean squared deviation from target. Expressions for the characteristic and probability mass functions of the adjustment interval are also given.     

A generalization of the Solis-Wets method

In this paper we focus on the application of global stochastic optimization methods to extremum estimators. We propose a general stochastic method—the master method—which includes several stochastic optimization algorithms as a particular case. The proposed method is sufficiently general to include the Solis-Wets method, the improving hit-and-run algorithm, and a stochastic version of the zigzag algorithm. A matrix formulation of the master method is presented and some specific results are given for the stochastic zigzag algorithm. Convergence of the proposed method is established under a mild set of conditions, and a simple regression model is used to illustrate the method.     

Underreporting of purchases of port wine

In this paper, we develop a new approach for modelling underreported Poisson counts. The parameters of the model are estimated by Markov chain Monte Carlo simulation. An application to a real data set from a Portuguese marketing survey illustrates the fruitfulness of the approach. We find that purchases of bottles of port wine increase significantly with income class and the size of the household.     

Carers and Professionals' Perspectives on Foster Care Outcomes: The Role of Contact

This study investigates the association between the contact of children or young people in care with their family, and the foster care placement evaluation (positive or negative) in Portugal. According to the perspectives of foster carers and service professionals' perceptions regarding children and young people's reactions, during and after the visits, are measured. Utilizing a quantitative approach, two fostering services teams and 140 foster carers completed questionnaires, which had 212 children in common. Results indicated that despite the importance of continued contact, especially for children and their parents, it was not determined to be essential to long-term placement. On one hand, there was the perception that a high percentage of children expressed positive reactions during and after the visit, while on the other hand, this didn't influence the perception of placement success. This study also showed significant differences between foster carers' and the professionals' perceptions on several dimensions of foster care, especially the children's reactions during visits. These differences need to be further analyzed in future research and the outcomes used to help improve contact management.