11 resultados para Bootstrap paramétrique

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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Industrial recurrent event data where an event of interest can be observed more than once in a single sample unit are presented in several areas, such as engineering, manufacturing and industrial reliability. Such type of data provide information about the number of events, time to their occurrence and also their costs. Nelson (1995) presents a methodology to obtain asymptotic confidence intervals for the cost and the number of cumulative recurrent events. Although this is a standard procedure, it can not perform well in some situations, in particular when the sample size available is small. In this context, computer-intensive methods such as bootstrap can be used to construct confidence intervals. In this paper, we propose a technique based on the bootstrap method to have interval estimates for the cost and the number of cumulative events. One of the advantages of the proposed methodology is the possibility for its application in several areas and its easy computational implementation. In addition, it can be a better alternative than asymptotic-based methods to calculate confidence intervals, according to some Monte Carlo simulations. An example from the engineering area illustrates the methodology.

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The Gumbel distribution is perhaps the most widely applied statistical distribution for problems in engineering. We propose a generalization-referred to as the Kumaraswamy Gumbel distribution-and provide a comprehensive treatment of its structural properties. We obtain the analytical shapes of the density and hazard rate functions. We calculate explicit expressions for the moments and generating function. The variation of the skewness and kurtosis measures is examined and the asymptotic distribution of the extreme values is investigated. Explicit expressions are also derived for the moments of order statistics. The methods of maximum likelihood and parametric bootstrap and a Bayesian procedure are proposed for estimating the model parameters. We obtain the expected information matrix. An application of the new model to a real dataset illustrates the potentiality of the proposed model. Two bivariate generalizations of the model are proposed.

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Assessment of the suitability of anthropogenic landscapes for wildlife species is crucial for setting priorities for biodiversity conservation. This study aimed to analyse the environmental suitability of a highly fragmented region of the Brazilian Atlantic Forest, one of the world's 25 recognized biodiversity hotspots, for forest bird species. Eight forest bird species were selected for the analyses, based on point counts (n = 122) conducted in April-September 2006 and January-March 2009. Six additional variables (landscape diversity, distance from forest and streams, aspect, elevation and slope) were modelled in Maxent for (1) actual and (2) simulated land cover, based on the forest expansion required by existing Brazilian forest legislation. Models were evaluated by bootstrap or jackknife methods and their performance was assessed by AUC, omission error, binomial probability or p value. All predictive models were statistically significant, with high AUC values and low omission errors. A small proportion of the actual landscape (24.41 +/- 6.31%) was suitable for forest bird species. The simulated landscapes lead to an increase of c. 30% in total suitable areas. In average, models predicted a small increase (23.69 +/- 6.95%) in the area of suitable native forest for bird species. Being close to forest increased the environmental suitability of landscapes for all bird species; landscape diversity was also a significant factor for some species. In conclusion, this study demonstrates that species distribution modelling (SDM) successfully predicted bird distribution across a heterogeneous landscape at fine spatial resolution, as all models were biologically relevant and statistically significant. The use of landscape variables as predictors contributed significantly to the results, particularly for species distributions over small extents and at fine scales. This is the first study to evaluate the environmental suitability of the remaining Brazilian Atlantic Forest for bird species in an agricultural landscape, and provides important additional data for regional environmental planning.

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Bovine coronavirus has been associated with diarrhoea in newborn calves, winter dysentery in adult cattle and respiratory tract infections in calves and feedlot cattle. In Cuba, the presence of BCoV was first reported in 2006. Since then, sporadic outbreaks have continued to occur. This study was aimed at deepening the knowledge of the evolution, molecular markers of virulence and epidemiology of BCoV in Cuba. A total of 30 samples collected between 2009 and 2011 were used for PCR amplification and direct sequencing of partial or full S gene. Sequence comparison and phylogenetic studies were conducted using partial or complete S gene sequences as phylogenetic markers. All Cuban bovine coronavirus sequences were located in a single cluster supported by 100% bootstrap and 1.00 posterior probability values. The Cuban bovine coronavirus sequences were also clustered with the USA BCoV strains corresponding to the GenBank accession numbers EF424621 and EF424623, suggesting a common origin for these viruses. This phylogenetic cluster was also the only group of sequences in which no recombination events were detected. Of the 45 amino acid changes found in the Cuban strains, four were unique. (C) 2012 Elsevier B.V. All rights reserved.

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Long-term survival models have historically been considered for analyzing time-to-event data with long-term survivors fraction. However, situations in which a fraction (1 - p) of systems is subject to failure from independent competing causes of failure, while the remaining proportion p is cured or has not presented the event of interest during the time period of the study, have not been fully considered in the literature. In order to accommodate such situations, we present in this paper a new long-term survival model. Maximum likelihood estimation procedure is discussed as well as interval estimation and hypothesis tests. A real dataset illustrates the methodology.

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During 2008D2010, ticks were collected from road-killed wild animals within the Serra dos Orgaos National Park area in the state of Rio de Janeiro, Brazil. In total, 193 tick specimens were collected, including Amblyomma dubitatum Neumann and Amblyomma cajennense (F.) from four Hydrochoerus hydrochaeris (L.), Amblyomma calcaratum Neumann and A. cajennense from four Tamandua tetradactyla (L.), Amblyomma aureolatum (Pallas) and A. cajennense from five Cerdocyon thous L., Amblyomma longirostre (Koch) from one Sphiggurus villosus (Cuvier), Amblyomma varium Koch from three Bradypus variegatus Schinz, and A. cajennense from one Buteogallus meridionalis (Latham). Molecular analyses based on polymerase chain reaction targeting two rickettsial genes (gltA and ompA) on tick DNA extracts showed that 70.6% (12/17) of the A. dubitatum adult ticks, and all Amblyomma sp. nymphal pools collected from capybaras were shown to contain rickettsial DNA, which after DNA sequencing, revealed to be 100% identical to the recently identified Rickettsia sp. strain Pampulha from A. dubitatum ticks collected in the state of Minas Gerais, Brazil. Phylogenetic analysis with concatenated sequences (gltA-ompA) showed that our sequence from A. dubitatum ticks, referred to Rickettsia sp. strain Serra dos Orgaos, segregated under 99% bootstrap support in a same cluster with Old World rickettsiae, namely R. tamurae, R. monacensis, and Rickettsia sp. strain 774e. Because A. dubitatum is known to bite humans, the potential role of Rickettsia sp. strain Serra dos Orgaos as human pathogen must be taken into account, because both R. tamurae and R. monacencis have been reported infecting human beings.

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Background Statistical methods for estimating usual intake require at least two short-term dietary measurements in a subsample of the target population. However, the percentage of individuals with a second dietary measurement (replication rate) may influence the precision of estimates, such as percentiles and proportions of individuals below cut-offs of intake. Objective To investigate the precision of the usual food intake estimates using different replication rates and different sample sizes. Participants/setting Adolescents participating in the continuous National Health and Nutrition Examination Survey 2007-2008 (n=1,304) who completed two 24-hour recalls. Statistical analyses performed The National Cancer Institute method was used to estimate the usual intake of dark green vegetables in the original sample comprising 1,304 adolescents with a replication rate of 100%. A bootstrap with 100 replications was performed to estimate CIs for percentiles and proportions of individuals below cut-offs of intake. Using the same bootstrap replications, four sets of data sets were sampled with different replication rates (80%, 60%, 40%, and 20%). For each data set created, the National Cancer Institute method was performed and percentiles, Cl, and proportions of individuals below cut-offs were calculated. Precision estimates were checked by comparing each Cl obtained from data sets with different replication rates with the Cl obtained from original data set. Further, we sampled 1,000, 750, 500, and 250 individuals from the original data set, and performed the same analytical procedures. Results Percentiles of intake and percentage of individuals below the cut-off points were similar throughout the replication rates and sample sizes, but the Cl increased as the replication rate decreased. Wider CIs were observed at 40% and 20% of replication rate. Conclusions The precision of the usual intake estimates decreased when low replication rates were used. However, even with different sample sizes, replication rates >40% may not lead to an important loss of precision. J Acad Nutr Diet. 2012;112:1015-1020.

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The development of new statistical and computational methods is increasingly making it possible to bridge the gap between hard sciences and humanities. In this study, we propose an approach based on a quantitative evaluation of attributes of objects in fields of humanities, from which concepts such as dialectics and opposition are formally defined mathematically. As case studies, we analyzed the temporal evolution of classical music and philosophy by obtaining data for 8 features characterizing the corresponding fields for 7 well-known composers and philosophers, which were treated with multivariate statistics and pattern recognition methods. A bootstrap method was applied to avoid statistical bias caused by the small sample data set, with which hundreds of artificial composers and philosophers were generated, influenced by the 7 names originally chosen. Upon defining indices for opposition, skewness and counter-dialectics, we confirmed the intuitive analysis of historians in that classical music evolved according to a master apprentice tradition, while in philosophy changes were driven by opposition. Though these case studies were meant only to show the possibility of treating phenomena in humanities quantitatively, including a quantitative measure of concepts such as dialectics and opposition, the results are encouraging for further application of the approach presented here to many other areas, since it is entirely generic.

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The self-consistency of a thermodynamical theory for hadronic systems based on the non-extensive statistics is investigated. We show that it is possible to obtain a self-consistent theory according to the asymptotic bootstrap principle if the mass spectrum and the energy density increase q-exponentially. A direct consequence is the existence of a limiting effective temperature for the hadronic system. We show that this result is in agreement with experiments. (C) 2012 Elsevier B.V. All rights reserved.

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Fraud is a global problem that has required more attention due to an accentuated expansion of modern technology and communication. When statistical techniques are used to detect fraud, whether a fraud detection model is accurate enough in order to provide correct classification of the case as a fraudulent or legitimate is a critical factor. In this context, the concept of bootstrap aggregating (bagging) arises. The basic idea is to generate multiple classifiers by obtaining the predicted values from the adjusted models to several replicated datasets and then combining them into a single predictive classification in order to improve the classification accuracy. In this paper, for the first time, we aim to present a pioneer study of the performance of the discrete and continuous k-dependence probabilistic networks within the context of bagging predictors classification. Via a large simulation study and various real datasets, we discovered that the probabilistic networks are a strong modeling option with high predictive capacity and with a high increment using the bagging procedure when compared to traditional techniques. (C) 2012 Elsevier Ltd. All rights reserved.

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Abstract Background Vampire bat related rabies harms both livestock industry and public health sector in central Brazil. The geographical distributions of vampire bat-transmitted rabies virus variants are delimited by mountain chains. These findings were elucidated by analyzing a high conserved nucleoprotein gene. This study aims to elucidate the detailed epidemiological characters of vampire bat-transmitted rabies virus by phylogenetic methods based on 619-nt sequence including unconserved G-L intergenic region. Findings The vampire bat-transmitted rabies virus isolates divided into 8 phylogenetic lineages in the previous nucleoprotein gene analysis were divided into 10 phylogenetic lineages with significant bootstrap values. The distributions of most variants were reconfirmed to be delimited by mountain chains. Furthermore, variants in undulating areas have narrow distributions and are apparently separated by mountain ridges. Conclusions This study demonstrates that the 619-nt sequence including G-L intergenic region is more useful for a state-level phylogenetic analysis of rabies virus than the partial nucleoprotein gene, and simultaneously that the distribution of vampire bat-transmitted RABV variants tends to be separated not only by mountain chains but also by mountain ridges, thus suggesting that the diversity of vampire bat-transmitted RABV variants was delimited by geographical undulations.