976 resultados para Bayesian approach
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INTRODUÇÃO: A malaria é uma doença endêmica na região da Amazônia Brasileira, e a detecção de possíveis fatores de risco pode ser de grande interesse às autoridades em saúde pública. O objetivo deste artigo é investigar a associação entre variáveis ambientais e os registros anuais de malária na região amazônica usando métodos bayesianos espaço-temporais. MÉTODOS: Utilizaram-se modelos de regressão espaço-temporais de Poisson para analisar os dados anuais de contagem de casos de malária entre os anos de 1999 a 2008, considerando a presença de alguns fatores como a taxa de desflorestamento. em uma abordagem bayesiana, as inferências foram obtidas por métodos Monte Carlo em cadeias de Markov (MCMC) que simularam amostras para a distribuição conjunta a posteriori de interesse. A discriminação de diferentes modelos também foi discutida. RESULTADOS: O modelo aqui proposto sugeriu que a taxa de desflorestamento, o número de habitants por km² e o índice de desenvolvimento humano (IDH) são importantes para a predição de casos de malária. CONCLUSÕES: É possível concluir que o desenvolvimento humano, o crescimento populacional, o desflorestamento e as alterações ecológicas associadas a estes fatores estão associados ao aumento do risco de malária. Pode-se ainda concluir que o uso de modelos de regressão de Poisson que capturam o efeito temporal e espacial em um enfoque bayesiano é uma boa estratégia para modelar dados de contagem de malária.
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We considered prediction techniques based on models of accelerated failure time with random e ects for correlated survival data. Besides the bayesian approach through empirical Bayes estimator, we also discussed about the use of a classical predictor, the Empirical Best Linear Unbiased Predictor (EBLUP). In order to illustrate the use of these predictors, we considered applications on a real data set coming from the oil industry. More speci - cally, the data set involves the mean time between failure of petroleum-well equipments of the Bacia Potiguar. The goal of this study is to predict the risk/probability of failure in order to help a preventive maintenance program. The results show that both methods are suitable to predict future failures, providing good decisions in relation to employment and economy of resources for preventive maintenance.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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O conhecimento do genoma pode auxiliar na identificação de regiões cromossômicas e, eventualmente, de genes que controlam características quantitativas (QTLs) de importância econômica. em um experimento com 1.129 suínos resultantes do cruzamento entre machos da raça Meishan e fêmeas Large White e Landrace, foram analisadas as características gordura intramuscular (GIM), em %, e ganho dos 25 aos 90 kg de peso vivo (GP), em g/dia, em 298 animais F1 e 831 F2, e espessura de toucinho (ET), em mm, em 324 F1 e 805 F2. Os animais das gerações F1 e F2 foram tipificados com 29 marcadores microsatélites. Estudou-se a ligação entre os cromossomos 4, 6 e 7 com GIM, ET e GP. Análises de QTL utilizando-se metodologia Bayesiana foram aplicadas mediante três modelos genéticos: modelo poligênico infinitesimal (MPI); modelo poligênico finito (MPF), considerando-se três locos; e MPF combinado com MPI. O número de QTLs, suas respectivas posições nos três cromossomos e o efeito fenotípico foram estimados simultaneamente. Os sumários dos parâmetros estimados foram baseados nas distribuições marginais a posteriori, obtidas por meio do uso da Cadeia de Markov, algoritmos de Monte Carlo (MCMC). Foi possível evidenciar dois QTLs relacionados a GIM nos cromossomos 4 e 6 e dois a ET nos cromossomos 4 e 7. Somente quando se ajustou o MPI, foram observados QTLs no cromossomo 4 para ET e GIM. Não foi possível detectar QTLs para a característica GP com a aplicação dessa metodologia, o que pode ter resultado do uso de marcadores não informativos ou da ausência de QTLs segregando nos cromossomos 4, 6 e 7 desta população. Foi evidenciada a vantagem de se analisar dados experimentais ajustando diferentes modelos genéticos; essas análises ilustram a utilidade e ampla aplicabilidade do método Bayesiano.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Data from purebred Simmental, Nellore and Canchim cattle breeds obtained from the respective Brazilian Associations of Breeders were used to estimate variance components and to predict genetic values for 365 days weight. The results obtained by Bayesian inference were compared to those from Restricted Maximum Likelihood (REML) and Best Linear Unbiased Prediction (BLUP), which are the most commonly used methods of estimation and prediction in animal breeding. The two methods presented similar point estimates but the study of the marginal posterior distributions in the Bayesian approach yields more detailed information about the parameters and other unknowns in the model.
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We introduce a new method to improve Markov maps by means of a Bayesian approach. The method starts from an initial map model, wherefrom a likelihood function is defined which is regulated by a temperature-like parameter. Then, the new constraints are added by the use of Bayes rule in the prior distribution. We applied the method to the logistic map of population growth of a single species. We show that the population size is limited for all ranges of parameters, allowing thus to overcome difficulties in interpretation of the concept of carrying capacity known as the Levins paradox. © Published under licence by IOP Publishing Ltd.
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Current research compares the Bayesian estimates obtained for the parameters of processes of ARCH family with normal and Student's t distributions for the conditional distribution of the return series. A non-informative prior distribution was adopted and a reparameterization of models under analysis was taken into account to map parameters' space into real space. The procedure adopts a normal prior distribution for the transformed parameters. The posterior summaries were obtained by Monte Carlo Markov Chain (MCMC) simulation methods. The methodology was evaluated by a series of Bovespa Index returns and the predictive ordinate criterion was employed to select the best adjustment model to the data. Results show that, as a rule, the proposed Bayesian approach provides satisfactory estimates and that the GARCH process with Student's t distribution adjusted better to the data.
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This study was conducted to examine the relationship among average annual productivity of the cow (PRODAM), yearling weight (YW), postweaning BW gain (PWG), scrotal circumference (SC), and stayability in the herd for at least 6 yr (STAY) of Nelore and composite beef cattle. Measurements were taken on animals born between 1980 and 2010 on 70 farms located in 7 Brazilian states. Estimates of heritability and genetic and environmental correlations were obtained by Bayesian approach with 5-trait animal models. Genetic trends were estimated by regressing means of estimated breeding values by year of birth. The heritability estimates were between 0.14 and 0.47. Estimates of genetic correlation among female traits (PRODAM and STAY) and growth traits ranged from-0.02 to 0.30. Estimates of genetic correlations ranged from 0.23 to 0.94 among growth traits indicating that selection for these traits could be successful in tropical breeding programs. Genetic correlations among all traits were favorable and simultaneous selection for growth, productivity, and stayability is therefore possible. Genetic correlation between PRODAM and STAY was 0.99 and 0.85 for Nelore and composite cattle, respectively. Therefore, PRODAM and STAY might be influenced by many of the same genes. The inclusion of PRODAM instead of STAY as a selection criterion seems to be more advantageous for tropical breeding programs because the generation interval required to obtain accurate estimates of genetic merit for PRODAM is shorter. Average annual genetic changes were greater in Nelore than in composite cattle. This was not unexpected because the breeding program of composite cattle included a large number of farms, different production environments, and genetic level of the herds and breeds. Thus, the selection process has become more difficult in this population. © 2013 American Society of Animal Science. All rights reserved.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Matematica Aplicada e Computacional - FCT
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Pós-graduação em Matematica Aplicada e Computacional - FCT
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Biplot graphics are widely employed in the study of the genotypeenvironment interactions, but they are only a graphical tool without a statistical hypothesis test. The singular values and scores (singular vectors) used in biplots correspond to specific estimates of its parameters, and the use of uncertainty measures may lead to different conclusions from those provided by a simple visual evaluation. The aim of this work is to estimate the genotype-environment interactions, using AMMI analysis, through Bayesian approach. Therefore the credibility intervals can be used for decision-making in different situations of analyses. It allows to verify the consistency of the selection and recommendation of cultivars. Two analyses were performed. The first analysis looked into 10 regular commercial hybrids and all possible 45 hybrids obtained from them. They were assessed in 15 locations. The second analysis evaluated 28 hybrids in 35 different environments, with imbalance data. The ellipses were grouped according to the standard of interaction in the biplot. The AMMI analysis with a Bayesian approach proved to be a complete analysis of stability and adaptability, which provides important information that may help the breeder in their decisions. The regions of credibility, built in the biplots, allow to perform an accurate selection and a precise genotype recommendation, with a level of credibility. Genotypes and environments can be grouped according to the existing interaction pattern, which makes possible to formulate specific recommendations. Moreover the environments can be evaluated, in order to find out which ones contribute similarly to the interaction and those to be discarted. The method makes possible to deal with imbalanced data in a natural way, showing efficiency for multienvironment trials. The prediction takes into account instability and the interaction standard of the observed data, in order to establish a direct comparison between genotypes of both 1st and 2nd seasons.
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Pós-graduação em Zootecnia - FMVZ