Influence diagnostics for the structural sharpe model under normal/independent distributions

A method is proposed in this paper to assess the local influence of minor perturbations for the Sharpe model when the normal distribution is replaced by normal/independent (NI) distributions. The family of NI distributions is an attractive class of symmetric heavy-tailed densities that includes as special cases the normal, t-Student, slash, and the contaminated normal distributions. Since the returns of the market are not observable, the statistical analysis is carried out in the context of an errors-in-variables model. An influence analysis for detecting influential observations (atypical returns) is developed to investigate the sensitivity of the maximum likelihood estimators. Diagnostic measures are obtained based on the conditional expectation of the complete-data log-likelihood function. The results are illustrated by using a set of shares of companies traded in the Chilean stock market.     

Simple and Conditional Discrimination and Specific Reinforcement in Teaching Reading: An Intervention Package

The Analysis of Verbal Behavior - This study evaluated an intervention package combining simple and conditional discrimination training and specific reinforcement for each stimulus class in...     

Hypotheses testing for structural calibration model

The main objective of this paper is to discuss maximum likelihood inference for the comparative structural calibration model (Barnett, in Biometrics 25:129–142, 1969), which is frequently used in the problem of assessing the relative calibrations and relative accuracies of a set of p instruments, each designed to measure the same characteristic on a common group of n experimental units. We consider asymptotic tests to answer the outlined questions. The methodology is applied to a real data set and a small simulation study is presented.     

Assessment of physical workload in boiler operations

The use of boiler wood-fired is fairly common equipment utilized in steam generation for energy production in small industries. The boiler activities are considered dangerous and heavy, mainly due to risks of explosions and the lack of mechanization of the process. This study assessed the burden of physical labor that operators of boilers are subjected during the workday. Assessment of these conditions was carried out through quantitative and qualitative measurements. A heart rate monitor, a wet-bulb globe thermometer (WBGT), a tape-measure and a digital infrared camera were the instruments used to collect the quantitative data. The Nordic Questionnaire and the Painful Areas Diagram were used to relate the health problems of the boiler operator with activity. With study, was concluded that the boiler activity may cause pains in the body of intensity different, muscle fatigue and diseases due to excessive weight and the exposure to heat. The research contributed to improve the boiler operator's workplace and working conditions.     

Evaluation of thermal overload in boiler operators

The Brazilians educational institutions need a large energy demand for the operation of laundries, restaurants and accommodation of students. Much of that energy comes from steam generated in boilers with wood fuel. The laboral activity in boiler may present problems for the operator's health due to exposure to excessive heat, and its operation has a high degree of risk. This paper describes an analysis made the conditions of thermal environment in the operation of a B category boiler, located at a Higher Education Institution, located in the Zona da Mata Mineira The equipments used to collect data were Meter WBGT of the Heat Index; Meter of Wet Bulb Index and Globe Thermometer (WBGT); Politeste Instruments, an anemometer and an Infrared Thermometer. By the application of questionnaires, the second phase consisted of collecting data on environmental factors (temperature natural environment, globe temperature, relative humidity and air velocity). The study concluded that during the period evaluated, the activity had thermal overload.     

Distributional Impacts of Pension Policy in Argentina: Winners and Losers within and Across Generations

The paper deals with the life‐cycle intra‐ and intergenerational income transfers operated by the pension system in Argentina by estimating the internal rates of return obtained by different generations and types of workers from their participation in the system. The empirical analysis confirms that earlier generations of workers benefited from higher social security returns than later generations, which retired under a matured system with large deficits. The worst‐affected cohorts were those born after 1920, particularly suffering from a social security crisis and falling real wages. For future generations retiring fully under the new mixed pension system, returns will more closely depend on financial market performance and the evolution of administration costs. Intragenerational transfers were also observed for all cohorts under study, as a result of the original system design as well as adjustments adopted during the implementation process. The real distributional impact of progressive benefit formulas could, however, be offset by state transfers to cover pension deficits and forward tax shifting in a context of unequal pension coverage.     

Switching nonparametric regression models

We propose a methodology to analyse data arising from a curve that, over its domain, switches among J states. We consider a sequence of response variables, where each response y depends on a covariate x according to an unobserved state z. The states form a stochastic process and their possible values are j=1,?…?, J. If z equals j the expected response of y is one of J unknown smooth functions evaluated at x. We call this model a switching nonparametric regression model. We develop an Expectation–Maximisation algorithm to estimate the parameters of the latent state process and the functions corresponding to the J states. We also obtain standard errors for the parameter estimates of the state process. We conduct simulation studies to analyse the frequentist properties of our estimates. We also apply the proposed methodology to the well-known motorcycle dataset treating the data as coming from more than one simulated accident run with unobserved run labels.     

Extending coverage under the Argentinian pension system: Distribution of access and prospects for universal coverage

One of the main challenges facing social policy in Latin American is to guarantee social security coverage for the entire population in the presence of a large informal sector. In Argentina, a regional pioneer in terms of the development of its pension system, more than one third of those of retirement age were without benefits in 2005. Since then, considerable progress has been made in extending coverage thanks to the introduction of a programme that has reduced contribution requirements and allocated benefits to a large number of seniors previously excluded from the system. This article analyzes the impact of this process in Argentina on the level and distribution of coverage, identifies changes in socio‐demographic factors which affect inclusion/exclusion in the social security system, and discusses remaining obstacles to the provision of universal coverage in the medium and long term.     

On diagnostics in multivariate measurement error models under asymmetric heavy-tailed distributions

In this paper, we discuss the extension of some diagnostic procedures to multivariate measurement error models with scale mixtures of skew-normal distributions (Lachos et?al., Statistics 44:541?C556, 2010c). This class provides a useful generalization of normal (and skew-normal) measurement error models since the random term distributions cover symmetric, asymmetric and heavy-tailed distributions, such as skew-t, skew-slash and skew-contaminated normal, among others. Inspired by the EM algorithm proposed by Lachos et?al. (Statistics 44:541?C556, 2010c), we develop a local influence analysis for measurement error models, following Zhu and Lee??s (J R Stat Soc B 63:111?C126, 2001) approach. This is because the observed data log-likelihood function associated with the proposed model is somewhat complex and Cook??s well-known approach can be very difficult to apply to achieve local influence measures. Some useful perturbation schemes are also discussed. In addition, a score test for assessing the homogeneity of the skewness parameter vector is presented. Finally, the methodology is exemplified through a real data set, illustrating the usefulness of the proposed methodology.