196 resultados para Poisson Mixed Model


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In this paper, we present different ofrailtyo models to analyze longitudinal data in the presence of covariates. These models incorporate the extra-Poisson variability and the possible correlation among the repeated counting data for each individual. Assuming a CD4 counting data set in HIV-infected patients, we develop a hierarchical Bayesian analysis considering the different proposed models and using Markov Chain Monte Carlo methods. We also discuss some Bayesian discrimination aspects for the choice of the best model.

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In this paper, we consider the problem of estimating the number of times an air quality standard is exceeded in a given period of time. A non-homogeneous Poisson model is proposed to analyse this issue. The rate at which the Poisson events occur is given by a rate function lambda(t), t >= 0. This rate function also depends on some parameters that need to be estimated. Two forms of lambda(t), t >= 0 are considered. One of them is of the Weibull form and the other is of the exponentiated-Weibull form. The parameters estimation is made using a Bayesian formulation based on the Gibbs sampling algorithm. The assignation of the prior distributions for the parameters is made in two stages. In the first stage, non-informative prior distributions are considered. Using the information provided by the first stage, more informative prior distributions are used in the second one. The theoretical development is applied to data provided by the monitoring network of Mexico City. The rate function that best fit the data varies according to the region of the city and/or threshold that is considered. In some cases the best fit is the Weibull form and in other cases the best option is the exponentiated-Weibull. Copyright (C) 2007 John Wiley & Sons, Ltd.

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Onion (Allium cepa) is one of the most cultivated and consumed vegetables in Brazil and its importance is due to the large laborforce involved. One of the main pests that affect this crop is the Onion Thrips (Thrips tabaci), but the spatial distribution of this insect, although important, has not been considered in crop management recommendations, experimental planning or sampling procedures. Our purpose here is to consider statistical tools to detect and model spatial patterns of the occurrence of the onion thrips. In order to characterize the spatial distribution pattern of the Onion Thrips a survey was carried out to record the number of insects in each development phase on onion plant leaves, on different dates and sample locations, in four rural properties with neighboring farms under different infestation levels and planting methods. The Mantel randomization test proved to be a useful tool to test for spatial correlation which, when detected, was described by a mixed spatial Poisson model with a geostatistical random component and parameters allowing for a characterization of the spatial pattern, as well as the production of prediction maps of susceptibility to levels of infestation throughout the area.

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Using the Berezin-Marinov pseudoclassical formulation of the spin particle we propose a classical model of spin noncommutativity. In the nonrelativistic case, the Poisson brackets between the coordinates are proportional to the spin angular momentum. The quantization of the model leads to the noncommutativity with mixed spatial and spin degrees of freedom. A modified Pauli equation, describing a spin half particle in an external electromagnetic field is obtained. We show that nonlocality caused by the spin noncommutativity depends on the spin of the particle; for spin zero, nonlocality does not appear, for spin half, Delta x Delta y >= theta(2)/2, etc. In the relativistic case the noncommutative Dirac equation was derived. For that we introduce a new star product. The advantage of our model is that in spite of the presence of noncommutativity and nonlocality, it is Lorentz invariant. Also, in the quasiclassical approximation it gives noncommutativity with a nilpotent parameter.

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The Brazilian Atlantic Forest is one of the richest biodiversity hotspots of the world. Paleoclimatic models have predicted two large stability regions in its northern and central parts, whereas southern regions might have suffered strong instability during Pleistocene glaciations. Molecular phylogeographic and endemism studies show, nevertheless, contradictory results: although some results validate these predictions, other data suggest that paleoclimatic models fail to predict stable rainforest areas in the south. Most studies, however, have surveyed species with relatively high dispersal rates whereas taxa with lower dispersion capabilities should be better predictors of habitat stability. Here, we have used two land planarian species as model organisms to analyse the patterns and levels of nucleotide diversity on a locality within the Southern Atlantic Forest. We find that both species harbour high levels of genetic variability without exhibiting the molecular footprint of recent colonization or population expansions, suggesting a long-term stability scenario. The results reflect, therefore, that paleoclimatic models may fail to detect refugia in the Southern Atlantic Forest, and that model organisms with low dispersal capability can improve the resolution of these models.

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This paper develops a Markovian jump model to describe the fault occurrence in a manipulator robot of three joints. This model includes the changes of operation points and the probability that a fault occurs in an actuator. After a fault, the robot works as a manipulator with free joints. Based on the developed model, a comparative study among three Markovian controllers, H(2), H(infinity), and mixed H(2)/H(infinity) is presented, applied in an actual manipulator robot subject to one and two consecutive faults.

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This paper addresses the development of a hybrid-mixed finite element formulation for the quasi-static geometrically exact analysis of three-dimensional framed structures with linear elastic behavior. The formulation is based on a modified principle of stationary total complementary energy, involving, as independent variables, the generalized vectors of stress-resultants and displacements and, in addition, a set of Lagrange multipliers defined on the element boundaries. The finite element discretization scheme adopted within the framework of the proposed formulation leads to numerical solutions that strongly satisfy the equilibrium differential equations in the elements, as well as the equilibrium boundary conditions. This formulation consists, therefore, in a true equilibrium formulation for large displacements and rotations in space. Furthermore, this formulation is objective, as it ensures invariance of the strain measures under superposed rigid body rotations, and is not affected by the so-called shear-locking phenomenon. Also, the proposed formulation produces numerical solutions which are independent of the path of deformation. To validate and assess the accuracy of the proposed formulation, some benchmark problems are analyzed and their solutions compared with those obtained using the standard two-node displacement/ rotation-based formulation.

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The facilities location problem for companies with global operations is very complex and not well explored in the literature. This work proposes a MILP model that solves the problem through minimization of the total logistic cost. Main contributions of the model are the pioneer carrying cost calculation, the treatment given to the take-or-pay costs and to the international tax benefits such as drawback and added value taxes in Brazil. The model was successfully applied to a real case of a chemical industry with industrial plants and sales all over the world. The model application recommended a totally new sourcing model for the company.

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In this paper we proposed a new two-parameters lifetime distribution with increasing failure rate. The new distribution arises on a latent complementary risk problem base. The properties of the proposed distribution are discussed, including a formal proof of its probability density function and explicit algebraic formulae for its reliability and failure rate functions, quantiles and moments, including the mean and variance. A simple EM-type algorithm for iteratively computing maximum likelihood estimates is presented. The Fisher information matrix is derived analytically in order to obtaining the asymptotic covariance matrix. The methodology is illustrated on a real data set. (C) 2010 Elsevier B.V. All rights reserved.

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The zero-inflated negative binomial model is used to account for overdispersion detected in data that are initially analyzed under the zero-Inflated Poisson model A frequentist analysis a jackknife estimator and a non-parametric bootstrap for parameter estimation of zero-inflated negative binomial regression models are considered In addition an EM-type algorithm is developed for performing maximum likelihood estimation Then the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and some ways to perform global influence analysis are derived In order to study departures from the error assumption as well as the presence of outliers residual analysis based on the standardized Pearson residuals is discussed The relevance of the approach is illustrated with a real data set where It is shown that zero-inflated negative binomial regression models seems to fit the data better than the Poisson counterpart (C) 2010 Elsevier B V All rights reserved

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Joint generalized linear models and double generalized linear models (DGLMs) were designed to model outcomes for which the variability can be explained using factors and/or covariates. When such factors operate, the usual normal regression models, which inherently exhibit constant variance, will under-represent variation in the data and hence may lead to erroneous inferences. For count and proportion data, such noise factors can generate a so-called overdispersion effect, and the use of binomial and Poisson models underestimates the variability and, consequently, incorrectly indicate significant effects. In this manuscript, we propose a DGLM from a Bayesian perspective, focusing on the case of proportion data, where the overdispersion can be modeled using a random effect that depends on some noise factors. The posterior joint density function was sampled using Monte Carlo Markov Chain algorithms, allowing inferences over the model parameters. An application to a data set on apple tissue culture is presented, for which it is shown that the Bayesian approach is quite feasible, even when limited prior information is available, thereby generating valuable insight for the researcher about its experimental results.

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Most biogeographical studies propose that southern temperate faunal disjunctions are either the result of vicariance of taxa originated in Gondwana or the result of transoceanic dispersal of taxa originated after the breakup of Gondwana. The aim of this paper is to show that this is a false dichotomy. Antarctica retained a mild climate until mid-Cenozoic and had lasting connections, notably with southern South America and Australia. Both taxa originally Gondwanan and taxa secondarily on Gondwanan areas were subjected to tectonic-induced vicariance, and there is no need to invoke ad hoc transoceanic dispersal, even for post-Gondwanan taxa. These different elements with circumantarctic distributions are here called `allochronic taxa` - taxa presently occupying the same area, but whose presence in that area does not belong to the same time period. This model allows accommodation of conflicting sources of evidence now available for many groups with circumantarctic distributions. The fact that the species from both layers are mixed up in the current biodiversity implies the need to use additional sources of evidence - such as biogeographical, palaeontological, geological and molecular - to discriminate which are the original Gondwanan and which are post-Gondwanan elements in austral landmasses.

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Bovine testicular hyalurphidase (BT-HAase), a tetrameric enzyme responsible for randomly hyaluronic acid, catalytic hydrolysis, was successfully immobilized on Langmuir- Blodgett films prepared with the sodium salt of dihexadacylphosphoric acid, (DHP-Zn(II)) ending with dipalmitoylphosphatidylcholine, DPPC. Data of protein, adsorption at the air-liquid interface by means of pendant drop shipe analysis and interaction of the protein with Langmuir monolayers of DPPC, using a Langmuir trough, have provided information. about the conditions to be used in the protein immobilization. The dynamic surface pressure curves obtained from pendant drop experiments for the enzyme in buffer solutions indicate that, within the range of concentration investigated in this study, the enzyme exhibits the largest induction time at 5 mu g L(-1) attributed to diffusion processes. Nevertheless, it seems that, at this concentration, the most probable conformation should be the one which occupies the smallest area at pi -> 0. The surface pressure (pi) area curves obtained for BT-HAase and mixed DPPC- BT-HAase monolayers reveal the presence of the enzyme at the air-lipid interface up to 45 mN m(-1). Tests of enzymatic activity, using hyaluronic acid, HA, as the substrate, showed an increase of activity compared to the homogeneous medium. A simplified model of protein insertion into the lipid matrix is used to explain the obtained results.

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Porphyrins are currently used in photodynamic therapy as photosensitizers. In this paper we studied the interaction of two charged porphyrins, 5, 10, 15, 20-mesotetrakis(N-metyl-4-pyridyl) porphyrin, (TMPyP/chloride salt) cationic, and 5, 10, 15, 20-meso-tetrakis(sulfonatophenyl) porphyrin, (TPPS(4)/sodium salt) anionic, nanoassembled in phospholipid Langmuir monolayers and Langmuir-Blodgett films. Furthermore, we used chitosan to mediate the interaction between the porphyrins and the model membrane, aiming to understand the role of the polysaccharide in a molecular level. The effect of the interaction of the photosensitizers on the fluidity of the lipid monolayer was investigated by using dilatational surface elasticity. We also used photoluminescence (PL) spectroscopy to identify the porphyrins adsorbed in the phospholipid films. We observed an expansion of the monolayer promoted by the adsorption of the porphyrins into the lipid-air interface which was more pronounced in the case of TMPyP, as a consequence of a strong electrostatic interaction with the anionic monolayer. The chitosan promoted a higher adsorption of the porphyrins on the phospholipid monolayers and enabled the porphyrin to stay in its monomeric form (as confirmed by PL spectroscopy), thus demonstrating that chitosan can be pointed out as a potential photosensitizer delivery system in photodynamic therapy.

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Motor unit action potentials (MUAPs) evoked by repetitive, low-intensity transcranial magnetic stimulation can be modeled as a Poisson process. A mathematical consequence of such a model is that the ratio of the variance to the mean of the amplitudes of motor evoked potentials (MEPs) should provide an estimate of the mean size of the individual MUAPs that summate to generate each MEP. We found that this is, in fact, the case. Our finding thus supports the use of the Poisson distribution to model MEP generation and indicates that this model enables characterization of the motor unit population that contributes to near-threshold MEPs. Muscle Nerve 42: 825-828, 2010