988 resultados para clustered binary data
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We review several asymmetrical links for binary regression models and present a unified approach for two skew-probit links proposed in the literature. Moreover, under skew-probit link, conditions for the existence of the ML estimators and the posterior distribution under improper priors are established. The framework proposed here considers two sets of latent variables which are helpful to implement the Bayesian MCMC approach. A simulation study to criteria for models comparison is conducted and two applications are made. Using different Bayesian criteria we show that, for these data sets, the skew-probit links are better than alternative links proposed in the literature.
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The second-order rate constants of thiolysis by n-heptanethiol on 4-nitro-N-n-butyl-1,8-naphthalimide (4NBN) are strongly affected by the water-methanol binary mixture composition reaching its maximum at around 50% mole fraction. In parallel solvent effects on 4NBN absorption molar extinction coefficient also shows a maximum at this composition region. From the spectroscopic study of reactant and product and the known H-bond capacity of the mixture a rationalization that involves specific solvent H-donor interaction with the nitro group is proposed to explain the kinetic data. Present findings also show a convenient methodology to obtain strongly fluorescent imides, valuable for peptide and analogs labeling as well as for thio-naphthalimide derivatives preparations. Copyright (C) 2008 John Wiley & Sons, Ltd.
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The objective of this study was to evaluate the use of probit and logit link functions for the genetic evaluation of early pregnancy using simulated data. The following simulation/analysis structures were constructed: logit/logit, logit/probit, probit/logit, and probit/probit. The percentages of precocious females were 5, 10, 15, 20, 25 and 30% and were adjusted based on a change in the mean of the latent variable. The parametric heritability (h²) was 0.40. Simulation and genetic evaluation were implemented in the R software. Heritability estimates (ĥ²) were compared with h² using the mean squared error. Pearson correlations between predicted and true breeding values and the percentage of coincidence between true and predicted ranking, considering the 10% of bulls with the highest breeding values (TOP10) were calculated. The mean ĥ² values were under- and overestimated for all percentages of precocious females when logit/probit and probit/logit models used. In addition, the mean squared errors of these models were high when compared with those obtained with the probit/probit and logit/logit models. Considering ĥ², probit/probit and logit/logit were also superior to logit/probit and probit/logit, providing values close to the parametric heritability. Logit/probit and probit/logit presented low Pearson correlations, whereas the correlations obtained with probit/probit and logit/logit ranged from moderate to high. With respect to the TOP10 bulls, logit/probit and probit/logit presented much lower percentages than probit/probit and logit/logit. The genetic parameter estimates and predictions of breeding values of the animals obtained with the logit/logit and probit/probit models were similar. In contrast, the results obtained with probit/logit and logit/probit were not satisfactory. There is need to compare the estimation and prediction ability of logit and probit link functions.
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The molar single ion activity coefficient (y(F)) of fluoride ions was determined at 25 degrees C and ionic strengths between 0.100 and 3.00 mol L(-1) NaClO(4) using an ion-selective electrode. The activity coefficient dependency on ionic strength was determined to be Phi(F) = log y(F) = 0.2315I-0.041I(2). The function Phi(F)(I), combined with functions obtained in previous work for copper (Phi(Cu)) and hydrogen (Phi(H)), allowed us to make the estimation of the stoichiometric and thermodynamic protonation constants of some halides and pseudo-halides as well as the formation constants of some pseudo-halides and fluoride 1:1 bivalent cation complexes. The calculation procedure proposed in this paper is consistent with critically-selected experimental data. It was demonstrated that it is possible to use Phi(F)(I) for predicting the thermodynamic equilibrium parameters independently of Pearson's hardness of acids and bases.
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Dynamic viscosity of binary mixtures of poly(ethylene glycol) molar mass 1500 da + water, potassium phosphate + water, and ternary mixtures of poly(ethylene glycol) molar mass 1500 da + potassium phosphate + water were determined at 303.15 K Binary and ternary mixture viscosities showed a direct logarithm-type relation with the increase of poly(ethylene glycol) and potassium phosphate contents. The models used for viscosity correlation gave a good fit to the experimental data.
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The molar single activity coefficients associated with propionate ion (Pr) have been determined at 25 degrees C and ionic strengths comprised between 0.300 and 3.00 M, adjusted with NaClO4, as background electrolyte. The investigation was carried out potentiometrically by using a second class Hg/Hg2Pr2 electrode. It was found that the dependence of propionate activity coefficients as a function of ionic strength (I) can be assessed through the following empirical equation: log y(Pr) = -0.185 I-3/2 + 0.104 I-2. Next, simple equations relating stoichiometric protonation constants of several monocarboxylates and formation constants associated with 1:1 complexes involving some bivalent cations and selected monocarboxylates, in aqueous solution, at 25 degrees C, as a function of ionic strength were derived, allowing the interconversion of parameters from one ionic strength to another, up to I = 3.00 M. In addition, thermodynamic formation constants as well as parameters associated with activity coefficients of the complex species in the equilibria are estimated. The body of results shows that the proposed calculation procedure is very consistent with critically selected experimental data.
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Simple equations were derived relating stoichiometric protonation constants of several monocarboxylates and formation constants associated with 1:1 complexes involving some bivalent cations and selected monocarboxylates, in aqueous sodium perchlorate media, at 25 degrees C, as a function of ionic strength (I), allowing the interconversion of parameters from one ionic strength to another, up to I = 3.00 M. In addition, thermodynamic formation constants as well as activity coefficients of the species involved in the equilibria were estimated. The results show that the proposed calculation procedure is very consistent with critically selected experimental data.
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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.
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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.
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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 in-viable for a exhaustive search. In this paper we propose a new nature-inspired feature selection technique based on the bats behaviour, which has never been applied to this context so far. The wrapper approach combines the power of exploration of the bats 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 five public datasets have demonstrated that the proposed approach can outperform some well-known swarm-based techniques. © 2012 IEEE.
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The rheological behavior of poly(ethylene glycol) of 1500 g·mol -1(PEG1500) aqueous solutions with various polymer concentrations (w = 0.05, 0.10, 0.15, 0.20 and 0.25) was studied at different temperatures (T = 283.15, 288.15, 293.15, 298.15 and 303.15) K. The analyses were carried out considering shear rates ranging from (20 to 350) s-1, using a cone-and-plate rheometer under controlled stress and temperature. Classical rheological models (Newton, Bingham, Power Law, Casson, and Herschel-Bulkley) were tested. The Power Law model was shown suitable to mathematically represent the rheological behavior of these solutions. Well-adjusted empirical models were derived for consistency index variations in function of temperature (Arrhenius-type model; R2 > 0.96), polymer concentration (exponential model; R2 > 0.99) or the combination of both (R 2 > 0.99). Additionally, linear models were used to represent the variations of behavior index in the functions of temperature (R2 > 0.83) and concentration (R2 > 0.87). © 2013 American Chemical Society.
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Feature selection aims to find the most important information to save computational efforts and data storage. We formulated this task as a combinatorial optimization problem since the exponential growth of possible solutions makes an exhaustive search infeasible. In this work, we propose a new nature-inspired feature selection technique based on bats behavior, namely, binary bat algorithm The wrapper approach combines the power of exploration of the bats together with the speed of the optimum-path forest classifier to find a better data representation. Experiments in public datasets have shown that the proposed technique can indeed improve the effectiveness of the optimum-path forest and outperform some well-known swarm-based techniques. © 2013 Copyright © 2013 Elsevier Inc. All rights reserved.
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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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We report results from a search for gravitational waves produced by perturbed intermediate mass black holes ( IMBH) in data collected by LIGO and Virgo between 2005 and 2010. The search was sensitive to astrophysical sources that produced damped sinusoid gravitational wave signals, also known as ringdowns, with frequency 50 <= f(0)/Hz <= 2000 and decay timescale 0.0001 less than or similar to tau/s less than or similar to 0.1 characteristic of those produced in mergers of IMBH pairs. No significant gravitational wave candidate was detected. We report upper limits on the astrophysical coalescence rates of IMBHs with total binary mass 50 <= M/ M circle dot <= 450 and component mass ratios of either 1: 1 or 4: 1. For systems with total mass 100 <= M/M circle dot <= 150, we report a 90% confidence upper limit on the rate of binary IMBH mergers with nonspinning and equal mass components of 6.9 x 10(-8) Mpc(-3) yr(-1). We also report a rate upper limit for ringdown waveforms from perturbed IMBHs, radiating 1% of their mass as gravitational waves in the fundamental, l = m = 2, oscillation mode, that is nearly three orders of magnitude more stringent than previous results.