Robust tests for the common principal components model

When dealing with several populations, the common principal components (CPC) model assumes equal principal axes but different variances along them. In this paper, a robust log-likelihood ratio statistic allowing to test the null hypothesis of a CPC model versus no restrictions on the scatter matrices is introduced. The proposal plugs into the classical log-likelihood ratio statistic robust scatter estimators. Using the same idea, a robust log-likelihood ratio and a robust Wald-type statistic for testing proportionality against a CPC model are considered. Their asymptotic distributions under the null hypothesis and their partial influence functions are derived. A small simulation study allows to compare the behavior of the classical and robust tests, under normal and contaminated data.     

Estimating utility functions using generalized maximum entropy

This paper estimates von Neumann and Morgenstern utility functions using the generalized maximum entropy (GME), applied to data obtained by utility elicitation methods. Given the statistical advantages of this approach, we provide a comparison of the performance of the GME estimator with ordinary least square (OLS) in a real data small sample setup. The results confirm the ones obtained for small samples through Monte Carlo simulations. The difference between the two estimators is small and it decreases as the width of the parameter support vector increases. Moreover, the GME estimator is more precise than the OLS one. Overall, the results suggest that GME is an interesting alternative to OLS in the estimation of utility functions when data are generated by utility elicitation methods.     

A Rule For Updating Ambiguous Beliefs

When preferences are such that there is no unique additive prior, the issue of which updating rule to use is of extreme importance. This paper presents an axiomatization of the rule which requires updating of all the priors by Bayes rule. The decision maker has conditional preferences over acts. It is assumed that preferences over acts conditional on event E happening, do not depend on lotteries received on E ^c, obey axioms which lead to maxmin expected utility representation with multiple priors, and have common induced preferences over lotteries. The paper shows that when all priors give positive probability to an event E, a certain coherence property between conditional and unconditional preferences is satisfied if and only if the set of subjective probability measures considered by the agent given E is obtained by updating all subjective prior probability measures using Bayes rule.     

The spatial distribution of smoking violations on a no-smoking campus: Implications for prevention

ABSTRACT

Objective: The present study extends research on campus smoking bans by examining where smokers are violating the policy at a large university in the southeastern region of the United States. Participants: The data collection was conducted by one graduate student from the university in August of 2014. Methods: A global positioning system device was used to collect the geo-coordinates of littered cigarette butts as a proxy measure for smoking violations. Results: A hot spot analysis found a number of spatial concentrations on campus, largely around classroom and administrative buildings along with parking lots and garages. Conclusions: The implications of such findings can direct enforcement to target these areas in order to reduce offenses and fulfill the initial goals of policy-makers and university administrators who support smoke-free campuses.     

Sample size for estimating a binomial proportion: comparison of different methods

The poor performance of the Wald method for constructing confidence intervals (CIs) for a binomial proportion has been demonstrated in a vast literature. The related problem of sample size determination needs to be updated and comparative studies are essential to understanding the performance of alternative methods. In this paper, the sample size is obtained for the Clopper–Pearson, Bayesian (Uniform and Jeffreys priors), Wilson, Agresti–Coull, Anscombe, and Wald methods. Two two-step procedures are used: one based on the expected length (EL) of the CI and another one on its first-order approximation. In the first step, all possible solutions that satisfy the optimal criterion are obtained. In the second step, a single solution is proposed according to a new criterion (e.g. highest coverage probability (CP)). In practice, it is expected a sample size reduction, therefore, we explore the behavior of the methods admitting 30% and 50% of losses. For all the methods, the ELs are inflated, as expected, but the coverage probabilities remain close to the original target (with few exceptions). It is not easy to suggest a method that is optimal throughout the range (0, 1) for p. Depending on whether the goal is to achieve CP approximately or above the nominal level different recommendations are made.     

Survival Weibull regression model for mismeasured outcomes

In some survival studies, the exact time of the event of interest is unknown, but the event is known to have occurred during a particular period of time (interval-censored data). If the diagnostic tool used to detect the event of interest is not perfectly sensitive and specific, outcomes may be mismeasured; a healthy subject may be diagnosed as sick and a sick one may be diagnosed as healthy. In such cases, traditional survival analysis methods produce biased estimates for the time-to-failure distribution parameters (Paggiaro and Torelli 2004 Paggiaro, A., and N. Torelli. 2004. The effect of classification errors in survival data analysis. Statistical Methods and Applications 13:213–25.[Crossref] , [Google Scholar]). In this context, we developed a parametric model that incorporates sensitivity and specificity into a grouped survival data analysis (a case of interval-censored data in which all subjects are tested at the same predetermined time points). Inferential aspects and properties of the methodology, such as the likelihood function and identifiability, are discussed in this article. Assuming known and non differential misclassification, Monte Carlo simulations showed that the proposed model performed well in the case of mismeasured outcomes; the estimates of the relative bias of the model were lower than those provided by the naive method that assumes perfect sensitivity and specificity. The proposed methodology is illustrated by a study related to mango tree lifetimes.     

Measuring the quality of economic forecasts

Most evaluations of forecasts have hitherto been primarily based on measure of statistical accuracy. Attention is drawn to the need for concentrating instead on the forecast components bearing on managerial decisions and on the economic effects of such decisions. The method suggested highlights the changing locus of the most influential errors over various time horizons. It also takes account of the economic consequences of under-estimates and over-estimates in forecasting, as well as of the penalties of belated correcting actions. Finally, some broader implications of this approach are discussed.     

Design of therapeutic clothing for sensory stimulation of children with psychomotor delay

This research work was based on an experimental concept of functional clothing for children with psychomotor development limitations. No matter the analyzed pathology, all these children need sensorial stimulation because of their psychomotor difficulties, especially at fine motor skills level. The main objective was to develop functional and comfortable clothing with sensorial stimulation elements (colours, textures, fragrances, sounds, etc.). It is intended, on the one hand, to increase the autonomy of the children in what concerns the act of dressing/undressing and, on the other hand, to stimulate their learning, coordination and self-esteem. A study about the specific needs of these children concerning clothing was worked out, which consisted in inquiring their parents and therapists. Based on the inquiries results, bibliographic revision in the area of therapeutic/ interactive clothing and analysis of didactic and therapeutic material catalogues we developed a clothing prototype (sweat-shirt). The prototype was then tested by the children of the study sample and the test results were, once again, explained by the parents through the fulfilling of a prototype evaluation inquiry. This study supplied some important conclusions, more directed to the confirmation of the theme significance and to the definition of a methodology to be used in future research.     

Eletrobras management program in ergonomics: the pursuit of excellence through maturity levels

Ergonomics for Eletrobras arose from the need in having an environment more suitable to the characteristics and circumstances of employees, in compliance with Regulation Standard no. 17 - Ergonomics (NR17) of the Ministry of Labor and Employment. Being a mixed economy company with regionalized anthropometric characteristics of its employees, the study of ergonomic adjustments and improvement of the concept of Ergonomics were and have been of great importance to the company's production environment. These advances have contributed to the development of specific technical criteria for the purchase of furniture and work tools (accessories), apart from their possible effects on the user. Ergonomics has been perceived as a technical-scientific tool, aimed to study labor interactions, new technologies and specific characteristics of the activities performed. To meet these demands a multidisciplinary Ergonomics Committee was created in Eletrobras, and effectively established the Ergonomics Management Program in the company; This program is marked by well-defined phases with great success in making use of these studies for other types of corporate activities and also facilitating the program control and its maturity levels, even at a business level.     

On a Class of Random Probability Measures with General Predictive Structure

Abstract. In this study, we investigate a recently introduced class of non‐parametric priors, termed generalized Dirichlet process priors. Such priors induce (exchangeable random) partitions that are characterized by a more elaborate clustering structure than those arising from other widely used priors. A natural area of application of these random probability measures is represented by species sampling problems and, in particular, prediction problems in genomics. To this end, we study both the distribution of the number of distinct species present in a sample and the distribution of the number of new species conditionally on an observed sample. We also provide the Bayesian Non‐parametric estimator for the number of new species in an additional sample of given size and for the discovery probability as function of the size of the additional sample. Finally, the study of its conditional structure is completed by the determination of the posterior distribution.