26 resultados para Dione Hutchinson
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Universidade Federal do Rio Grande do Norte
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To investigate the possibilities and limits of mechanisms of participativa management in the scope of the Pronaf - National Program of Fortalecimento of Familiar Agriculture, and the corresponding effectiveness of its actions in the construction of alternatives of sustainable agricultural development in the Coast North of the State of the Great River of the North, more specifically, in the composed Subzona de Touros for the cities of Bulls, White Well, Pureness, Is Miguel of the Gostoso and Taipu. To carry through this analysis they had been carried through Research of Field with the objective to reconstitute the trajectory of the CMDRS, to trace the profile of the citizens that compose each one of the five advice, its expectations, interests and the level of participation of the local population
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The chart of control of Hotelling T2 has been the main statistical device used in monitoring multivariate processes. Currently the technological development of control systems and automation enabled a high rate of collection of information of the production systems in very short time intervals, causing a dependency between the results of observations. This phenomenon known as auto correlation causes in the statistical control of the multivariate processes a high rate of false alarms, prejudicing in the chart performance. This entails the violation of the assumption of independence and normality of the distribution. In this thesis we considered not only the correlation between two variables, but also the dependence between observations of the same variable, that is, auto correlation. It was studied by simulation, the bi variate case and the effect of auto correlation on the performance of the T2 chart of Hotelling.
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We considered prediction techniques based on models of accelerated failure time with random e ects for correlated survival data. Besides the bayesian approach through empirical Bayes estimator, we also discussed about the use of a classical predictor, the Empirical Best Linear Unbiased Predictor (EBLUP). In order to illustrate the use of these predictors, we considered applications on a real data set coming from the oil industry. More speci - cally, the data set involves the mean time between failure of petroleum-well equipments of the Bacia Potiguar. The goal of this study is to predict the risk/probability of failure in order to help a preventive maintenance program. The results show that both methods are suitable to predict future failures, providing good decisions in relation to employment and economy of resources for preventive maintenance.
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In survival analysis, the response is usually the time until the occurrence of an event of interest, called failure time. The main characteristic of survival data is the presence of censoring which is a partial observation of response. Associated with this information, some models occupy an important position by properly fit several practical situations, among which we can mention the Weibull model. Marshall-Olkin extended form distributions other a basic generalization that enables greater exibility in adjusting lifetime data. This paper presents a simulation study that compares the gradient test and the likelihood ratio test using the Marshall-Olkin extended form Weibull distribution. As a result, there is only a small advantage for the likelihood ratio test
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In this work we study the accelerated failure-time generalized Gamma regression models with a unified approach. The models attempt to estimate simultaneously the effects of covariates on the acceleration/deceleration of the timing of a given event and the surviving fraction. The method is implemented in the free statistical software R. Finally the model is applied to a real dataset referring to the time until the return of the disease in patients diagnosed with breast cancer
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This paper proposes a new control chart to monitor a process mean employing a combined npx-X control chart. Basically the procedure consists of splitting the sample of size n into two sub-samples n1 and n2 determined by an optimization search. The sampling occur in two-stages. In the first stage the units of the sub-sample n1 are evaluated by attributes and plotted in npx control chart. If this chart signs then units of second sub-sample are measured and the monitored statistic plotted in X control chart (second stage). If both control charts sign then the process is stopped for adjustment. The possibility of non-inspection in all n items may promote a reduction not only in the cost but also the time spent to examine the sampled items. Performances of the current proposal, individual X and npx control charts are compared. In this study the proposed procedure presents many competitive options for the X control chart for a sample size n and a shift from the target mean. The average time to sign (ATS) of the current proposal lower than the values calculated from an individual X control chart points out that the combined control chart is an efficient tool in monitoring process mean.
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Survival models deals with the modeling of time to event data. However in some situations part of the population may be no longer subject to the event. Models that take this fact into account are called cure rate models. There are few studies about hypothesis tests in cure rate models. Recently a new test statistic, the gradient statistic, has been proposed. It shares the same asymptotic properties with the classic large sample tests, the likelihood ratio, score and Wald tests. Some simulation studies have been carried out to explore the behavior of the gradient statistic in fi nite samples and compare it with the classic statistics in diff erent models. The main objective of this work is to study and compare the performance of gradient test and likelihood ratio test in cure rate models. We first describe the models and present the main asymptotic properties of the tests. We perform a simulation study based on the promotion time model with Weibull distribution to assess the performance of the tests in finite samples. An application is presented to illustrate the studied concepts
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
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Survival models deals with the modelling of time to event data. In certain situations, a share of the population can no longer be subjected to the event occurrence. In this context, the cure fraction models emerged. Among the models that incorporate a fraction of cured one of the most known is the promotion time model. In the present study we discuss hypothesis testing in the promotion time model with Weibull distribution for the failure times of susceptible individuals. Hypothesis testing in this model may be performed based on likelihood ratio, gradient, score or Wald statistics. The critical values are obtained from asymptotic approximations, which may result in size distortions in nite sample sizes. This study proposes bootstrap corrections to the aforementioned tests and Bartlett bootstrap to the likelihood ratio statistic in Weibull promotion time model. Using Monte Carlo simulations we compared the nite sample performances of the proposed corrections in contrast with the usual tests. The numerical evidence favors the proposed corrected tests. At the end of the work an empirical application is presented.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)