Bayesian binary regression model: an application to in-hospital death after AMI prediction

Um modelo bayesiano de regressão binária é desenvolvido para predizer óbito hospitalar em pacientes acometidos por infarto agudo do miocárdio. Métodos de Monte Carlo via Cadeias de Markov (MCMC) são usados para fazer inferência e validação. Uma estratégia para construção de modelos, baseada no uso do fator de Bayes, é proposta e aspectos de validação são extensivamente discutidos neste artigo, incluindo a distribuição a posteriori para o índice de concordância e análise de resíduos. A determinação de fatores de risco, baseados em variáveis disponíveis na chegada do paciente ao hospital, é muito importante para a tomada de decisão sobre o curso do tratamento. O modelo identificado se revela fortemente confiável e acurado, com uma taxa de classificação correta de 88% e um índice de concordância de 83%.

Bayesian outlier analysis in binary regression

We propose alternative approaches to analyze residuals in binary regression models based on random effect components. Our preferred model does not depend upon any tuning parameter, being completely automatic. Although the focus is mainly on accommodation of outliers, the proposed methodology is also able to detect them. Our approach consists of evaluating the posterior distribution of random effects included in the linear predictor. The evaluation of the posterior distributions of interest involves cumbersome integration, which is easily dealt with through stochastic simulation methods. We also discuss different specifications of prior distributions for the random effects. The potential of these strategies is compared in a real data set. The main finding is that the inclusion of extra variability accommodates the outliers, improving the adjustment of the model substantially, besides correctly indicating the possible outliers.

A note on model uncertainty in linear regression

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.

A comparison of statistical methods for genomic selection in a mice population

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Improving methods in gap ecology: Revisiting size and shape distributions using a model selection approach

Questions: We assess gap size and shape distributions, two important descriptors of the forest disturbance regime, by asking: which statistical model best describes gap size distribution; can simple geometric forms adequately describe gap shape; does gap size or shape vary with forest type, gap age or the method used for gap delimitation; and how similar are the studied forests and other tropical and temperate forests? Location: Southeastern Atlantic Forest, Brazil. Methods: Analysing over 150 gaps in two distinct forest types (seasonal and rain forests), a model selection framework was used to select appropriate probability distributions and functions to describe gap size and gap shape. The first was described using univariate probability distributions, whereas the latter was assessed based on the gap area-perimeter relationship. Comparisons of gap size and shape between sites, as well as size and age classes were then made based on the likelihood of models having different assumptions for the values of their parameters. Results: The log-normal distribution was the best descriptor of gap size distribution, independently of the forest type or gap delimitation method. Because gaps became more irregular as they increased in size, all geometric forms (triangle, rectangle and ellipse) were poor descriptors of gap shape. Only when small and large gaps (> 100 or 400m2 depending on the delimitation method) were treated separately did the rectangle and isosceles triangle become accurate predictors of gap shape. Ellipsoidal shapes were poor descriptors. At both sites, gaps were at least 50% longer than they were wide, a finding with important implications for gap microclimate (e.g. light entrance regime) and, consequently, for gap regeneration. Conclusions: In addition to more appropriate descriptions of gap size and shape, the model selection framework used here efficiently provided a means by which to compare the patterns of two different types of forest. With this framework we were able to recommend the log-normal parameters μ and σ for future comparisons of gap size distribution, and to propose possible mechanisms related to random rates of gap expansion and closure. We also showed that gap shape varied highly and that no single geometric form was able to predict the shape of all gaps, the ellipse in particular should no longer be used as a standard gap shape. © 2012 International Association for Vegetation Science.

Minimizing inter-genotypic competition effects to predict genetic values and selection in forestry genetic tests

The effect of competition is an important source of variation in breeding experiments. This study aimed to compare the selection of plants of open-pollinated families of Eucalyptus with and without the use of competition covariables. Genetic values were determined for each family and tree and for the traits height, diameter at breast height and timber volume in a randomized block design, resulting in the variance components, genetic parameters, selection gains, effective size and selection coincidence, with and without the use of covariables. Intergenotypic competition is an important factor of environmental variation. The use of competition covariables generally reduces the estimates of variance components and influences genetic gains in the studied traits. Intergenotypic competition biases the selection of open-pollinated eucalypt progenies, and can result in an erroneous choice of superior genotypes; the inclusion of covariables in the model reduces this influence.

To be or not to be . . . a flower? A test of possible cues influencing hunting site selection in subadult females of the crab spider Epicadus heterogaster (Guerin 1812) (Araneae: Thomisidae)

Females of some Thomisidae species are known to use visual and olfactory stimuli to select high quality hunting sites. However, because studies about foraging behavior in this family are concentrated on a few species, the comprehension of the process related to hunting behavior evolution in crab spiders may be biased. In this study we investigated the hunting site selection of a previously unstudied crab spider, Epicadus heterogaster. We performed three experiments to evaluate the hypothesis that subadult females are able to use visual and olfactory stimuli to select hunting sites. In the first experiment, females did not preferentially select flower paper models that matched their body coloration. However, after choosing a model that had the same body color as the spider, they remained on it for longer periods than on models with different colors. In the second experiment, females did not discriminate between flower paper models, natural flower models and crumpled paper models. Females did also not discriminate among different olfactory stimuli in the third experiment. It is possible that subadult females of E. heterogaster need to establish and experience a given hunting site before evaluating its quality. However, it remains to be investigated if they use UV cues to select a foraging area before experiencing it.

Methods to verify parameter equality in nonlinear regression models

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Molecular model for the binary complex of uropepsin and pepstatin

The three-dimensional structure of human uropepsin complexed with pepstatin has been modelled using human pepsin as a template. Uropepsin is an aspartic proteinase from the urine, produced in the form of pepsinogen A in the gastric mucosa. The structure is bilobal, consisting of two predominantly beta -sheet lobes which, as observed in other aspartic proteinases, are related by a pseudo twofold axis. A structural comparison between binary complexes of pepsin:pepstatin and uropepsin:pepstatin is discussed. (C) 2001 Academic Press.

Phonons in binary BCC lithium-sodium alloys

The dispersion relations along the principal symmetry directions in BCC lithium-sodium alloys are calculated using second-order perturbation theory. The local modified Hoshino-Youngmodel potential was used for the lithium and the local Harrison model potential for sodium. The phonon density of states, the root mean square displacements and (Θ-T) curves are also calculated. In the absence of experimental data, just the theoretical predictions are presented here.

Optimizing feature selection through binary charged system search

Feature selection aims to find the most important information from a given set of features. As this task can be seen as an optimization problem, the combinatorial growth of the possible solutions may be inviable for a exhaustive search. In this paper we propose a new nature-inspired feature selection technique based on the Charged System Search (CSS), which has never been applied to this context so far. The wrapper approach combines the power of exploration of CSS together with the speed of the Optimum-Path Forest classifier to find the set of features that maximizes the accuracy in a validating set. Experiments conducted in four public datasets have demonstrated the validity of the proposed approach can outperform some well-known swarm-based techniques. © 2013 Springer-Verlag.

Multivariate analysis for animal selection in experimental research

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Microencapsulation of turmeric oleoresin in binary and ternary blends of gum arabic, maltodextrin and modified starch

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

On the optical flow model selection through metaheuristics

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Model selection for discriminative restricted boltzmann machines through meta-heuristic techniques

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)