923 resultados para model selection in binary regression


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

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Feature selection has been actively pursued in the last years, since to find the most discriminative set of features can enhance the recognition rates and also to make feature extraction faster. In this paper, the propose a new feature selection called Binary Cuckoo Search, which is based on the behavior of cuckoo birds. The experiments were carried out in the context of theft detection in power distribution systems in two datasets obtained from a Brazilian electrical power company, and have demonstrated the robustness of the proposed technique against with several others nature-inspired optimization techniques. © 2013 IEEE.

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We suggest a time-dependent mean-field hydrodynamic model for a binary dipolar boson-fermion mixture to study the stability and collapse of fermions in the 164Dy-161Dy mixture. The condition of stability of the dipolar mixture is illustrated in terms of phase diagrams. A collapse is induced in a disk-shaped stable binary mixture by jumping the interspecies contact interaction from repulsive to attractive by the Feshbach resonance technique. The subsequent dynamics is studied by solving the time-dependent mean-field model including three-body loss due to molecule formation in boson-fermion and boson-boson channels. Collapse and fragmentation in the fermions after subsequent explosions are illustrated. The anisotropic dipolar interaction leads to anisotropic fermionic density distribution during collapse. This study is carried out in three-dimensional space using realistic values of dipolar and contact interactions. © 2013 American Physical Society.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The aim of this study is to investigate the genetic control of growth traits in the initial phases of development in fragmented populations of Copaifera langsdorffii Desf., using microsatellite markers. For the effect two populations of C. langsdorffii were used: a municipal park located in Sao Jose do Rio Preto (SJRP) and at Assis Ecological Station (AES), both in the state of sao Paulo, Brazil. The model to estimate the heritability coefficient is the method of regression of a measure of phenotypic similarity and an estimate of kinship between paired individuals. The coefficients of relatedness and heritability were estimated for three classes of distance (10, 20 and 30 m) within populations. Estimates of heritability were low (maximum 0.15) for all traits, ranging from positive values for regenerating individuals of the population SJRP and from negative to positive for the juvenile population AES. In evolutionary terms, these results indicate little chance of changing the population mean of the characters studied by natural selection; with strong random environmental effects changing this average. The results also suggest that the heritability for height to decrease between regenerating to juvenile stage and the natural selection in natural populations is stronger in the early stages of plant development.

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The prevalence of anxiety and depression disorders in undergraduate students is high and several variables can be influential. The aim is to verify the predictive value of social skills, sociodemographic variables, and course characteristics for depression and anxiety. A total of 1282 students of a public university, of both sexes and from different years and courses, participated in this study. Screening instruments for depression and anxiety were applied, as well as an instrument investigating social skills and a questionnaire covering socio demographic indicators and course characteristics. The data were analyzed using univariate analysis followed by multiple binary regression analysis in order to define the relevance of these depression and anxiety measures. The rates of anxiety and depression were 19.4% and 3.8%, respectively. The social skills and living situation were predictive of depression, with the social skills and course area (with higher prevalence for the exact and human sciences) remaining in the final model for anxiety. Such data have implications for psychological prevention and intervention with this population.

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In this paper we propose a hybrid hazard regression model with threshold stress which includes the proportional hazards and the accelerated failure time models as particular cases. To express the behavior of lifetimes the generalized-gamma distribution is assumed and an inverse power law model with a threshold stress is considered. For parameter estimation we develop a sampling-based posterior inference procedure based on Markov Chain Monte Carlo techniques. We assume proper but vague priors for the parameters of interest. A simulation study investigates the frequentist properties of the proposed estimators obtained under the assumption of vague priors. Further, some discussions on model selection criteria are given. The methodology is illustrated on simulated and real lifetime data set.

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In this paper, a new family of survival distributions is presented. It is derived by considering that the latent number of failure causes follows a Poisson distribution and the time for these causes to be activated follows an exponential distribution. Three different activation schemes are also considered. Moreover, we propose the inclusion of covariates in the model formulation in order to study their effect on the expected value of the number of causes and on the failure rate function. Inferential procedure based on the maximum likelihood method is discussed and evaluated via simulation. The developed methodology is illustrated on a real data set on ovarian cancer.

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Information on the solvation in mixtures of water, W, and the ionic liquids, ILs, 1-allyl-3-R-imidazolium chlorides; R = methyl, 1-butyl, and 1-hexyl, has been obtained from the responses of the following solvatochromic probes: 2,6-dibromo-4-[(E)-2-(1-R-pyridinium-4-yl)ethenyl] phenolate, R = methyl, MePMBr2; 1-octyl, OcPMBr(2), and the corresponding quinolinium derivative, MeQMBr(2). A model developed for solvation in binary mixtures of W and molecular solvents has been extended to the present mixtures. Our objective is to assess the relevance to solvation of hydrogen-bonding and the hydrophobic character of the IL and the solvatochromic probe. Plots of the medium empirical polarity, E-T(probe) versus its composition revealed non-ideal behavior, attributed to preferential solvation by the IL and, more efficiently, by the IL-W hydrogen-bonded complex. The deviation from linearity increases as a function of increasing number of carbon atoms in the alkyl group of the IL, and is larger than that observed for solvation by W plus molecular solvents (1-propanol and 2-(1-butoxy)ethanol) that are more hydrophobic than the ILs investigated. This enhanced deviation is attributed to the more organized structure of the ILs proper, which persists in their aqueous solutions. MeQMBr(2) is more susceptible to solvent lipophilicity than OcPMBr(2), although the former probe is less lipophilic. This enhanced susceptibility agrees with the important effect of annelation on the contributions of the quinonoid and zwitterionic limiting structures to the ground and excited states of the probe, hence on its response to both medium composition and lipophilicity of the IL.

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Dapsone (DAP) is a synthetic sulfone drug with bacteriostatic activity, mainly against Mycobacterium leprae. In this study we have investigated the interactions of DAP with cyclodextrins, 2-hydroxypropyl-beta-cyclodextrin (HP beta CD) and beta-cyclodextrin (beta CD), in the presence and absence of water-soluble polymers, in order to improve its solubility and bioavailability. Solid systems DAP/HP beta CD and DAP/beta CD, in the presence or absence of polyvinylpyrrolidone (PVP K30) or hydroxypropyl methylcellulose (HPMC), were prepared. The binary and ternary systems were evaluated and characterized by SEM, DSC, XRD and NMR analysis as well as phase solubility assays, in order to investigate the interactions between DAP and the excipients in aqueous solution. This study revealed that inclusion complexes of DAP and cyclodextrins (HP beta CD and beta CD) can be produced in order to improve DAP solubility and bioavailability in the presence or absence of polymers (PVP K30 and HPMC). The more stable inclusion complex was obtained with HP beta CD, and consequently HP beta CD was more efficient in improving DAP solubility than beta CD, and the addition of polymers had no influence on DAP solubility or on the stability of the DAP/CDs complexes.

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This paper proposes a general class of regression models for continuous proportions when the data contain zeros or ones. The proposed class of models assumes that the response variable has a mixed continuous-discrete distribution with probability mass at zero or one. The beta distribution is used to describe the continuous component of the model, since its density has a wide range of different shapes depending on the values of the two parameters that index the distribution. We use a suitable parameterization of the beta law in terms of its mean and a precision parameter. The parameters of the mixture distribution are modeled as functions of regression parameters. We provide inference, diagnostic, and model selection tools for this class of models. A practical application that employs real data is presented. (C) 2011 Elsevier B.V. All rights reserved.

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Statistical approaches to evaluate higher order SNP-SNP and SNP-environment interactions are critical in genetic association studies, as susceptibility to complex disease is likely to be related to the interaction of multiple SNPs and environmental factors. Logic regression (Kooperberg et al., 2001; Ruczinski et al., 2003) is one such approach, where interactions between SNPs and environmental variables are assessed in a regression framework, and interactions become part of the model search space. In this manuscript we extend the logic regression methodology, originally developed for cohort and case-control studies, for studies of trios with affected probands. Trio logic regression accounts for the linkage disequilibrium (LD) structure in the genotype data, and accommodates missing genotypes via haplotype-based imputation. We also derive an efficient algorithm to simulate case-parent trios where genetic risk is determined via epistatic interactions.