913 resultados para grouping estimators
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Reductions in firing costs are often advocated as a way of increasingthe dynamism of labour markets in both developed and less developed countries. Evidence from Europe and the U.S. on the impact of firing costs has, however, been mixed. Moreover, legislative changes both in Europe and the U.S. have been limited. This paper, instead, examines the impact of the Colombian Labour Market Reform of 1990, which substantially reduced dismissal costs. I estimate the incidence of a reduction in firing costs on worker turnover by exploiting the temporal change in the Colombian labour legislation as well as the variability in coverage between formal and informal sector workers. Using a grouping estimator to control for common aggregate shocks and selection, I find that the exit hazard rates into and out of unemployment increased after the reform by over 1% for formal workers (covered by the legislation) relative to informal workers (uncovered). The increase of the hazards implies a net decrease in unemployment of a third of a percentage point, which accounts for about one quarter of the fall in unemployment during the period of study.
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The present contribution explores the impact of the QUALIS metric system for academic evaluation implemented by CAPES (Coordination for the Development of Personnel in Higher Education) upon Brazilian Zoological research. The QUALIS system is based on the grouping and ranking of scientific journals according to their Impact Factor (IF). We examined two main points implied by this system, namely: 1) its reliability as a guideline for authors; 2) if Zoology possesses the same publication profile as Botany and Oceanography, three fields of knowledge grouped by CAPES under the subarea "BOZ" for purposes of evaluation. Additionally, we tested CAPES' recent suggestion that the area of Ecology would represent a fourth field of research compatible with the former three. Our results indicate that this system of classification is inappropriate as a guideline for publication improvement, with approximately one third of the journals changing their strata between years. We also demonstrate that the citation profile of Zoology is distinct from those of Botany and Oceanography. Finally, we show that Ecology shows an IF that is significantly different from those of Botany, Oceanography, and Zoology, and that grouping these fields together would be particularly detrimental to Zoology. We conclude that the use of only one parameter of analysis for the stratification of journals, i.e., the Impact Factor calculated for a comparatively small number of journals, fails to evaluate with accuracy the pattern of publication present in Zoology, Botany, and Oceanography. While such simplified procedure might appeals to our sense of objectivity, it dismisses any real attempt to evaluate with clarity the merit embedded in at least three very distinct aspects of scientific practice, namely: productivity, quality, and specificity.
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This article deals with the efficiency of fractional integration parameter estimators. This study was based on Monte Carlo experiments involving simulated stochastic processes with integration orders in the range]-1,1[. The evaluated estimation methods were classified into two groups: heuristics and semiparametric/maximum likelihood (ML). The study revealed that the comparative efficiency of the estimators, measured by the lesser mean squared error, depends on the stationary/non-stationary and persistency/anti-persistency conditions of the series. The ML estimator was shown to be superior for stationary persistent processes; the wavelet spectrum-based estimators were better for non-stationary mean reversible and invertible anti-persistent processes; the weighted periodogram-based estimator was shown to be superior for non-invertible anti-persistent processes.
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The study, part of the project "Atherosclerotic cardiovascular diseases, lipemic disorders, hypertension, obesity and diabetis mellitus in a population of the metropolitan area of the southeastern region of Brazil", had the following objectives: a) the characterization and distribution among typical human socio-economic groupings, of the prevalence of some particular habits which constitute aspects of life-style-the use of tobacco, the use of alcohol and sedentary activity; b) the establishment of the interrelation between the above-mentioned habits and some lipemic disorders. The prevalence of the habits cited behaved in the following manner: the use of tobacco predominated among men, distributed uniformly throughout the social strata; among the women the average percentage of smokers was 18,9%, a significant difference occurring among the highest socio-economic class, where the average was of 40.2%. The sedentary style of life presented high prevalence, among both men and women with exception of the women of the highest socio-economic level and of the skilled working class. The use of alcohol, as one would expect, is a habit basically practised by the men, without any statistically significant differences between classes. For the purpose of establishing associations between these risk fictors and lipemic conditions four situations were chosen, of the following characteristics: 1- total cholesterol > or = 220 mg/dl and triglycerides > or = 150 mg/dl; 2- HDL cholesterol <35 mg/dl for men and <45 mg/dl for women and triglycerides levels > or = 150 mg/dl; 3- HDL cholesterol <35 mg/dl for men and <45 mg/dl for women and triglycerides levels <150 mg/dl; 4- total cholesterol 220 mg/dl with triglycerides levels <150 mg/dl. Six models of multiple (backward) regression were established, with seven independent variables- age, sex, use of tobacco, consumption of alcohol, light physical activity, hypertension and obesity. Significant associations (P<0,05) were revealed with hypercholesterolemia, accompanied by triglyceride levels > or = 150 mg/dl, and the following independent variables: age, use of tobacco and the interactions between obesity and smoking, age and sedentary lifestyle, sex and obesity (R2=22%); the standardized B coefficient showed that the variables with the greatest weight in the forecasting of the variation in the levels of cholesterol were smoking and the interaction between obesity and smoking. The hypercholesterolemia accompanied by triglycerides levels <150 mg/dl showed a positive association between total cholesterol and sex and the interactions obesity/smoking and sex/obesity. As regards HDL cholesterol accompanied by triglyceride/ levels > or = 150 mg/dl was inversely associated with obesity and the interaction smoking/ age and directly with age (R=31%). The standardized B coeffients, indicated that the variables obesity and the interactions smoking/age possessed a weight three times greater than age alone in accounting for the variation in the serum levels of HDL cholesterol. When accompanied by triglycerides <150 mg/dl there was no association between and the independent variables and the set of them presented R equal to 22%. The sum of top, in the population stutied in this project, the component habits of life-style (smoking, alcohol consumption and sedentary activity) which constitute risk factors which determine morbidity from atherosclerotic cardiovascular diseases are be found distributed through all the typical social groupings of this particular form of social organization. On the other hand, the seven independent variables used in the multiple regression models for the explanation of the lipemic conditions considered presented multiple determination coefficients which varied, approximately, between 20% and 30%. Thus it is important that in the genetic epidemiology the study of the morbidities in question be emphasized.
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Copyright © 2014 The Authors. Methods in Ecology and Evolution © 2014 British Ecological Society.
RadiaLE: A framework for designing and assessing link quality estimators in wireless sensor networks
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Stringent cost and energy constraints impose the use of low-cost and low-power radio transceivers in large-scale wireless sensor networks (WSNs). This fact, together with the harsh characteristics of the physical environment, requires a rigorous WSN design. Mechanisms for WSN deployment and topology control, MAC and routing, resource and mobility management, greatly depend on reliable link quality estimators (LQEs). This paper describes the RadiaLE framework, which enables the experimental assessment, design and optimization of LQEs. RadiaLE comprises (i) the hardware components of the WSN testbed and (ii) a software tool for setting-up and controlling the experiments, automating link measurements gathering through packets-statistics collection, and analyzing the collected data, allowing for LQEs evaluation. We also propose a methodology that allows (i) to properly set different types of links and different types of traffic, (ii) to collect rich link measurements, and (iii) to validate LQEs using a holistic and unified approach. To demonstrate the validity and usefulness of RadiaLE, we present two case studies: the characterization of low-power links and a comparison between six representative LQEs. We also extend the second study for evaluating the accuracy of the TOSSIM 2 channel model.
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Link quality estimation is a fundamental building block for the design of several different mechanisms and protocols in wireless sensor networks (WSN). A thorough experimental evaluation of link quality estimators (LQEs) is thus mandatory. Several WSN experimental testbeds have been designed ([1–4]) but only [3] and [2] targeted link quality measurements. However, these were exploited for analyzing low-power links characteristics rather than the performance of LQEs. Despite its importance, the experimental performance evaluation of LQEs remains an open problem, mainly due to the difficulty to provide a quantitative evaluation of their accuracy. This motivated us to build a benchmarking testbed for LQE - RadiaLE, which we present here as a demo. It includes (i.) hardware components that represent the WSN under test and (ii.) a software tool for the set up and control of the experiments and also for analyzing the collected data, allowing for LQEs evaluation.
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Locomotor tasks characterization plays an important role in trying to improve the quality of life of a growing elderly population. This paper focuses on this matter by trying to characterize the locomotion of two population groups with different functional fitness levels (high or low) while executing three different tasks-gait, stair ascent and stair descent. Features were extracted from gait data, and feature selection methods were used in order to get the set of features that allow differentiation between functional fitness level. Unsupervised learning was used to validate the sets obtained and, ultimately, indicated that it is possible to distinguish the two population groups. The sets of best discriminate features for each task are identified and thoroughly analysed. Copyright © 2014 SCITEPRESS - Science and Technology Publications. All rights reserved.
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Submitted in partial fulfillment for the Requirements for the Degree of PhD in Mathematics, in the Speciality of Statistics in the Faculdade de Ciências e Tecnologia
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The Hausman (1978) test is based on the vector of differences of two estimators. It is usually assumed that one of the estimators is fully efficient, since this simplifies calculation of the test statistic. However, this assumption limits the applicability of the test, since widely used estimators such as the generalized method of moments (GMM) or quasi maximum likelihood (QML) are often not fully efficient. This paper shows that the test may easily be implemented, using well-known methods, when neither estimator is efficient. To illustrate, we present both simulation results as well as empirical results for utilization of health care services.
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The effects of structural breaks in dynamic panels are more complicated than in time series models as the bias can be either negative or positive. This paper focuses on the effects of mean shifts in otherwise stationary processes within an instrumental variable panel estimation framework. We show the sources of the bias and a Monte Carlo analysis calibrated on United States bank lending data demonstrates the size of the bias for a range of auto-regressive parameters. We also propose additional moment conditions that can be used to reduce the biases caused by shifts in the mean of the data.
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We introduce simple nonparametric density estimators that generalize theclassical histogram and frequency polygon. The new estimators are expressed as linear combination of density functions that are piecewisepolynomials, where the coefficients are optimally chosen in order to minimize the integrated square error of the estimator. We establish the asymptotic behaviour of the proposed estimators, and study theirperformance in a simulation study.
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We compare a set of empirical Bayes and composite estimators of the population means of the districts (small areas) of a country, and show that the natural modelling strategy of searching for a well fitting empirical Bayes model and using it for estimation of the area-level means can be inefficient.