907 resultados para Model selection criteria


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We consider model selection uncertainty in linear regression. We study theoretically and by simulation the approach of Buckland and co-workers, who proposed estimating a parameter common to all models under study by taking a weighted average over the models, using weights obtained from information criteria or the bootstrap. This approach is compared with the usual approach in which the 'best' model is used, and with Bayesian model averaging. The weighted predictor behaves similarly to model averaging, with generally more realistic mean-squared errors than the usual model-selection-based estimator.

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Abstract Background The criteria for organ sharing has developed a system that prioritizes liver transplantation (LT) for patients with hepatocellular carcinoma (HCC) who have the highest risk of wait-list mortality. In some countries this model allows patients only within the Milan Criteria (MC, defined by the presence of a single nodule up to 5 cm, up to three nodules none larger than 3 cm, with no evidence of extrahepatic spread or macrovascular invasion) to be evaluated for liver transplantation. This police implies that some patients with HCC slightly more advanced than those allowed by the current strict selection criteria will be excluded, even though LT for these patients might be associated with acceptable long-term outcomes. Methods We propose a mathematical approach to study the consequences of relaxing the MC for patients with HCC that do not comply with the current rules for inclusion in the transplantation candidate list. We consider overall 5-years survival rates compatible with the ones reported in the literature. We calculate the best strategy that would minimize the total mortality of the affected population, that is, the total number of people in both groups of HCC patients that die after 5 years of the implementation of the strategy, either by post-transplantation death or by death due to the basic HCC. We illustrate the above analysis with a simulation of a theoretical population of 1,500 HCC patients with tumor size exponentially. The parameter λ obtained from the literature was equal to 0.3. As the total number of patients in these real samples was 327 patients, this implied in an average size of 3.3 cm and a 95% confidence interval of [2.9; 3.7]. The total number of available livers to be grafted was assumed to be 500. Results With 1500 patients in the waiting list and 500 grafts available we simulated the total number of deaths in both transplanted and non-transplanted HCC patients after 5 years as a function of the tumor size of transplanted patients. The total number of deaths drops down monotonically with tumor size, reaching a minimum at size equals to 7 cm, increasing from thereafter. With tumor size equals to 10 cm the total mortality is equal to the 5 cm threshold of the Milan criteria. Conclusion We concluded that it is possible to include patients with tumor size up to 10 cm without increasing the total mortality of this population.

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In linear mixed models, model selection frequently includes the selection of random effects. Two versions of the Akaike information criterion (AIC) have been used, based either on the marginal or on the conditional distribution. We show that the marginal AIC is no longer an asymptotically unbiased estimator of the Akaike information, and in fact favours smaller models without random effects. For the conditional AIC, we show that ignoring estimation uncertainty in the random effects covariance matrix, as is common practice, induces a bias that leads to the selection of any random effect not predicted to be exactly zero. We derive an analytic representation of a corrected version of the conditional AIC, which avoids the high computational cost and imprecision of available numerical approximations. An implementation in an R package is provided. All theoretical results are illustrated in simulation studies, and their impact in practice is investigated in an analysis of childhood malnutrition in Zambia.

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The principal aim of this paper is to examine the criteria assisting in the selection of biomass for energy generation in Brazil. To reach the aim, this paper adopts case study and survey research methods to collect information from four biomass energy case companies and solicits opinions from experts. The data gathered are analysed in line with a wide range of related data, including selection criteria for biomass and its importance, energy policies in Brazil, availability of biomass feedstock in Brazil and its characteristics, as well as status quo of biomass-based energy in Brazil. The findings of the paper demonstrate that there are ten main criteria in biomass selection for energy generation in Brazil. They comprise geographical conditions, availability of biomass feedstock, demand satisfaction, feedstock costs and oil prices, energy content of biomass feedstock, business and economic growth, CO2 emissions of biomass end-products, effects on soil, water and biodiversity, job creation and local community support, as well as conversion technologies. Furthermore, the research also found that these main criteria cannot be grouped on the basis of sustainability criteria, nor ranked by their importance as there is correlation between each criterion such as a cause and effect relationship, as well as some overlapping areas. Consequently, this means that when selecting biomass more comprehensive consideration is advisable.

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Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnoloigia, 2016.

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Survival or longevity is an economically important trait in beef cattle. The main inconvenience for its inclusion in selection criteria is delayed recording of phenotypic data and the high computational demand for including survival in proportional hazard models. Thus, identification of a longevity-correlated trait that could be recorded early in life would be very useful for selection purposes. We estimated the genetic relationship of survival with productive and reproductive traits in Nellore cattle, including weaning weight (WW), post-weaning growth (PWG), muscularity (MUSC), scrotal circumference at 18 months (SC18), and heifer pregnancy (HP). Survival was measured in discrete time intervals and modeled through a sequential threshold model. Five independent bivariate Bayesian analyses were performed, accounting for cow survival and the five productive and reproductive traits. Posterior mean estimates for heritability (standard deviation in parentheses) were 0.55 (0.01) for WW, 0.25 (0.01) for PWG, 0.23 (0.01) for MUSC, and 0.48 (0.01) for SC18. The posterior mean estimates (95% confidence interval in parentheses) for the genetic correlation with survival were 0.16 (0.13-0.19), 0.30 (0.25-0.34), 0.31 (0.25-0.36), 0.07 (0.02-0.12), and 0.82 (0.78-0.86) for WW, PWG, MUSC, SC18, and HP, respectively. Based on the high genetic correlation and heritability (0.54) posterior mean estimates for HP, the expected progeny difference for HP can be used to select bulls for longevity, as well as for post-weaning gain and muscle score.

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Context tree models have been introduced by Rissanen in [25] as a parsimonious generalization of Markov models. Since then, they have been widely used in applied probability and statistics. The present paper investigates non-asymptotic properties of two popular procedures of context tree estimation: Rissanen's algorithm Context and penalized maximum likelihood. First showing how they are related, we prove finite horizon bounds for the probability of over- and under-estimation. Concerning overestimation, no boundedness or loss-of-memory conditions are required: the proof relies on new deviation inequalities for empirical probabilities of independent interest. The under-estimation properties rely on classical hypotheses for processes of infinite memory. These results improve on and generalize the bounds obtained in Duarte et al. (2006) [12], Galves et al. (2008) [18], Galves and Leonardi (2008) [17], Leonardi (2010) [22], refining asymptotic results of Buhlmann and Wyner (1999) [4] and Csiszar and Talata (2006) [9]. (C) 2011 Elsevier B.V. All rights reserved.

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The selection criteria for Euler-Bernoulli or Timoshenko beam theories are generally given by means of some deterministic rule involving beam dimensions. The Euler-Bernoulli beam theory is used to model the behavior of flexure-dominated (or ""long"") beams. The Timoshenko theory applies for shear-dominated (or ""short"") beams. In the mid-length range, both theories should be equivalent, and some agreement between them would be expected. Indeed, it is shown in the paper that, for some mid-length beams, the deterministic displacement responses for the two theories agrees very well. However, the article points out that the behavior of the two beam models is radically different in terms of uncertainty propagation. In the paper, some beam parameters are modeled as parameterized stochastic processes. The two formulations are implemented and solved via a Monte Carlo-Galerkin scheme. It is shown that, for uncertain elasticity modulus, propagation of uncertainty to the displacement response is much larger for Timoshenko beams than for Euler-Bernoulli beams. On the other hand, propagation of the uncertainty for random beam height is much larger for Euler beam displacements. Hence, any reliability or risk analysis becomes completely dependent on the beam theory employed. The authors believe this is not widely acknowledged by the structural safety or stochastic mechanics communities. (C) 2010 Elsevier Ltd. All rights reserved.

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The glass-forming ability (GFA) of metallic alloys is associated with a topological instability criterion combined with a new parameter based on the average electronegativity difference of an element and its surrounding neighbours. In this model, we assume that during solidification the glassy phase competes directly with the supersaturated solid solution having the lowest topological instability factor for a given composition. This criterion is combined with the average electronegativity difference among the elements in the alloy, which reflects the strength of the liquid. The GFA is successfully correlated with this combined criterion in several binary glass-forming systems.

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With the advent of multi-fibre spectrographs such as the 'Two-Degree Field' (2dF) instrument at the Angle-Australian Telescope, quasar surveys that are free of any preselection of candidates and any biases this implies have become possible for the first time. The first of these is that which is being undertaken as part of the Fornax Spectroscopic Survey, a survey of the area around the Fornax Cluster of galaxies, and aims to obtain the spectra of all objects in the magnitude range 16.5 < b(j) < 19.7. To date, 3679 objects in the central pi -deg(2) area have been successfully identified from their spectral characteristics. Of these, 71 are found to be quasars, 61 with redshifts 0.3 < z < 2.2 and 10 with redshifts z > 2.2. Using this complete quasar sample, a new determination of quasar number counts is made, enabling an independent check of existing quasars surveys. Cumulative counts per square degree at a magnitude limit of b(j) < 19.5 are found to be 11.5 +/- 2.2 for 0.3 < z < 2.2, 2.22 +/- 0.93 for z > 2.2 and 13.7 +/- 3.1 for z > 0.3. Given the likely detection of extra quasars in the Fornax survey, we make a more detailed examination of existing quasar selection techniques. First, looking at the use of a stellar criterion, four of the 71 quasars are 'non-stellar' on the basis of the automated plate measuring facility (APM) b(j) classification, however inspection shows all are consistent with stellar, but misclassified due to image confusion. Examining the ultraviolet excess and multicolour selection techniques, for the selection criteria investigated, ultraviolet excess would find 69 +/- 6 per cent of our 0.3 < z < 2.2 quasars and only 50(-18)(+14), per cent of our z > 2.2 quasars, while the completeness level for multicolour selection is found to be 90(-4)(+3) per cent for 0.3 < z < 2.2 quasars and 80(-12)(+14) per cent for z > 2.2 quasars. The extra quasars detected by our all-object survey thus have unusually red star-like colours, and this appears to be a result of the continuum shape rather than any emission features. An intrinsic dust extinction model may, at least partly, account for the red colours.

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Selection criteria for lung donation were based on initial experiences with lung transplantation without further studies to improve them, thereby guaranting the best use of donated organs. A definition of an extended criteria donor is therefore required to obtain more lungs to meet the demands of patients awaiting transplantation. Studies have been reviewed for the impact on survival and morbidity of age ranges, oxygen fraction, cause of death, smoking habits, x-ray findings, infection, hepatitis serology and non-heart-beating status, seeking to support physicians to make decisions regarding the use of marginal organs.

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Objective: Several limitations of published bioelectrical impedance analysis (BIA) equations have been reported. The aims were to develop in a multiethnic, elderly population a new prediction equation and cross-validate it along with some published BIA equations for estimating fat-free mass using deuterium oxide dilution as the reference method. Design and setting: Cross-sectional study of elderly from five developing countries. Methods: Total body water (TBW) measured by deuterium dilution was used to determine fat-free mass (FFM) in 383 subjects. Anthropometric and BIA variables were also measured. Only 377 subjects were included for the analysis, randomly divided into development and cross-validation groups after stratified by gender. Stepwise model selection was used to generate the model and Bland Altman analysis was used to test agreement. Results: FFM = 2.95 - 3.89 (Gender) + 0.514 (Ht(2)/Z) + 0.090 (Waist) + 0.156 (Body weight). The model fit parameters were an R(2), total F-Ratio, and the SEE of 0.88, 314.3, and 3.3, respectively. None of the published BIA equations met the criteria for agreement. The new BIA equation underestimated FFM by just 0.3 kg in the cross-validation sample. The mean of the difference between FFM by TBW and the new BIA equation were not significantly different; 95% of the differences were between the limits of agreement of -6.3 to 6.9 kg of FFM. There was no significant association between the mean of the differences and their averages (r = 0.008 and p = 0.2). Conclusions: This new BIA equation offers a valid option compared with some of the current published BIA equations to estimate FFM in elderly subjects from five developing countries.

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The total meat yield in a beef cattle production cycle is economically very important and depends on the number of calves born per year or birth season, being directly related to reproductive potential. Accumulated Productivity (ACP) is an index that expresses a cow`s capacity to give birth regularly at a young age and to wean animals of greater body weight. Using data from cattle participating in the ""Program for Genetic Improvement of the Nelore Breed"" (PMGRN - Nelore Brasil), bi-trait analyses were performed using the Restricted Maximum Likelihood method based on an ACP animal model and the following traits: age at first calving (AFC), female body weight adjusted for 365 (BW365) and 450 (BW450) days of age, and male scrotal circumference adjusted for 365 (SC365), 450 (SC450), 550 (SC550) and 730 (SC730) days of age. Median estimated ACP heritability was 0.19 and the genetic correlations with AFC, BW365, BW450, SC365, SC450, SC550 and SC730 were 0.33, 0.70, 0.65, 0.08, 0.07, 0.12 and 0.16, respectively. ACP increased and AFC decreased over time, revealing that the selection criteria genetically improved these traits. Selection based on ACP appears to favor the heaviest females at 365 and 450 days of age who showed better reproductive performance as regards AFC. Scrotal circumference was not genetically associated with ACP. (C) 2007 Elsevier B.V. All rights reserved.

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Os fundos de investimento imobiliário combinam características tanto do mercado imobiliário, fonte de seus rendimentos, quanto do mercado de capitais, ambiente em que são negociados. O impacto de cada um desses mercados subjacentes no comportamento, desempenho e risco dessa classe de ativos não é, no entanto, ainda claramente definida, sendo um dos grandes temas em análise, tanto na literatura acadêmica, quanto na indústria de fundos internacionais. Em face da significativa expansão dessa alternativa de investimento no mercado brasileiro, no presente estudo foram analisadas as variáveis que influenciam os retornos dos fundos imobiliários brasileiros para uma amostra de fundos listados em Bolsa de Valores de São Paulo, período de 2008-2013. Seguindo a metodologia de Clayton e Mackinnon (2003), os fatores explicativos dos retornos foram decompostos em quatro componentes principais, sendo três fatores de retorno de mercado (mercado de ações, mercado de renda fixa e mercado imobiliário) e risco idiossincrático. De acordo com a estatística descritiva, os fundos imobiliários da amostra apresentaram maior retorno em relação aos demais mercados, exceto em comparação com o mercado imobiliário, porém com menor risco. As análises de correlação, regressão e decomposição da variância indicam que o mercado de ações e o mercado imobiliário direto são, em geral, significativos no modelo, porém explicam apenas cerca de 15% da volatilidade dos retornos dos fundos da amostra. À luz da Moderna Teoria do Portfólio, esses resultados indicam que a inclusão de fundos imobiliários pode ter potencial diversificador numa carteira multi-ativo, seja aumentando o retorno total de uma carteira formada de ações e títulos de renda fixa, sem acréscimo em risco; ou mantendo o retorno dessa carteira, com diminuição da volatilidade, ampliando assim a fronteira eficiente da carteira. Esse efeito questiona o tradicional equilibrium fund de carteiras de investimentos formadas apenas de ações e renda fixa e aponta os fundos imobiliários como uma alternativa de investimento diversificadora, enquanto classe de ativo única. A análise de subamostras por tipologia indica, porém, que o papel diversificador dos fundos imobiliários está atrelado ao tipo de empreendimento que lastreia esse fundo, uma vez que os fatores explicativos e seus impactos nos retornos diferem de uma tipologia para outra. Esse resultado tem importantes implicações no critério de seleção a ser adotado tanto por investidores para seleção de ativos para uma carteira otimizada, como para gestores de fundos imobiliários na formatação e gestão desses produtos. Conclui-se também que os retornos dos fundos, de certo modo, refletem seu caráter híbrido, mas o modelo decomposto em 4 componentes não é suficiente para explicar os retornos dos fundos imobiliários, uma vez que o modelo estendido, demonstrou que outras variáveis, inclusive parâmetros desses próprios mercados, além de variáveis macroeconômicas e as características de cada fundo (eg. market-to-book, tamanho), podem ser responsáveis por explicar considerável parte da variância dos retornos dos FIIs.