27 resultados para MCMC.

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)


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Neste artigo apresentamos uma análise Bayesiana para o modelo de volatilidade estocástica (SV) e uma forma generalizada deste, cujo objetivo é estimar a volatilidade de séries temporais financeiras. Considerando alguns casos especiais dos modelos SV usamos algoritmos de Monte Carlo em Cadeias de Markov e o software WinBugs para obter sumários a posteriori para as diferentes formas de modelos SV. Introduzimos algumas técnicas Bayesianas de discriminação para a escolha do melhor modelo a ser usado para estimar as volatilidades e fazer previsões de séries financeiras. Um exemplo empírico de aplicação da metodologia é introduzido com a série financeira do IBOVESPA.

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Background: Hepatitis C virus (HCV) is an important human pathogen affecting around 3% of the human population. In Brazil, it is estimated that there are approximately 2 to 3 million HCV chronic carriers. There are few reports of HCV prevalence in Rondonia State (RO), but it was estimated in 9.7% from 1999 to 2005. The aim of this study was to characterize HCV genotypes in 58 chronic HCV infected patients from Porto Velho, Rondonia (RO), Brazil. Methods: A fragment of 380 bp of NS5B region was amplified by nested PCR for genotyping analysis. Viral sequences were characterized by phylogenetic analysis using reference sequences obtained from the GenBank (n = 173). Sequences were aligned using Muscle software and edited in the SE-AL software. Phylogenetic analyses were conducted using Bayesian Markov chain Monte Carlo simulation (MCMC) to obtain the MCC tree using BEAST v. 1.5.3. Results: From 58 anti-HCV positive samples, 22 were positive to the NS5B fragment and successfully sequenced. Genotype 1b was the most prevalent in this population (50%), followed by 1a (27.2%), 2b (13.6%) and 3a (9.0%). Conclusions: This study is the first report of HCV genotypes from Rondonia State and subtype 1b was found to be the most prevalent. This subtype is mostly found among people who have a previous history of blood transfusion but more detailed studies with a larger number of patients are necessary to understand the HCV dynamics in the population of Rondonia State, Brazil.

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Background: Hepatitis B virus (HBV) can be classified into nine genotypes (A-I) defined by sequence divergence of more than 8% based on the complete genome. This study aims to identify the genotypic distribution of HBV in 40 HBsAg-positive patients from Rondonia, Brazil. A fragment of 1306 bp partially comprising surface and polymerase overlapping genes was amplified by PCR. Amplified DNA was purified and sequenced. Amplified DNA was purified and sequenced on an ABI PRISM (R) 377 Automatic Sequencer (Applied Biosystems, Foster City, CA, USA). The obtained sequences were aligned with reference sequences obtained from the GenBank using Clustal X software and then edited with Se-Al software. Phylogenetic analyses were conducted by the Markov Chain Monte Carlo (MCMC) approach using BEAST v.1.5.3. Results: The subgenotypes distribution was A1 (37.1%), D3 (22.8%), F2a (20.0%), D4 (17.1%) and D2 (2.8%). Conclusions: These results for the first HBV genotypic characterization in Rondonia state are consistent with other studies in Brazil, showing the presence of several HBV genotypes that reflects the mixed origin of the population, involving descendants from Native Americans, Europeans, and Africans.

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Background: The Brazilian population is mainly descendant from European colonizers, Africans and Native Americans. Some Afro-descendants lived in small isolated communities since the slavery period. The epidemiological status of HBV infection in Quilombos communities from northeast of Brazil remains unknown. The aim of this study was to characterize the HBV genotypes circulating inside a Quilombo isolated community from Maranhao State, Brazil. Methods: Seventy-two samples from Frechal Quilombo community at Maranhao were collected. All serum samples were screened by enzyme-linked immunosorbent assays for the presence of hepatitis B surface antigen ( HBsAg). HBsAg positive samples were submitted to DNA extraction and a fragment of 1306 bp partially comprising HBsAg and polymerase coding regions (S/POL) was amplified by nested PCR and its nucleotide sequence was determined. Viral isolates were genotyped by phylogenetic analysis using reference sequences from each genotype obtained from GenBank (n = 320). Sequences were aligned using Muscle software and edited in the SE-AL software. Bayesian phylogenetic analyses were conducted using Markov Chain Monte Carlo (MCMC) method to obtain the MCC tree using BEAST v.1.5.3. Results: Of the 72 individuals, 9 (12.5%) were HBsAg-positive and 4 of them were successfully sequenced for the 1306 bp fragment. All these samples were genotype A1 and grouped together with other sequences reported from Brazil. Conclusions: The present study represents the first report on the HBV genotypes characterization of this community in the Maranhao state in Brazil where a high HBsAg frequency was found. In this study, we reported a high frequency of HBV infection and the exclusive presence of subgenotype A1 in an Afro-descendent community in the Maranhao State, Brazil.

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Background: GB virus C (GBV-C) is an enveloped positive-sense ssRNA virus belonging to the Flaviviridae family. Studies on the genetic variability of the GBV-C reveals the existence of six genotypes: genotype 1 predominates in West Africa, genotype 2 in Europe and America, genotype 3 in Asia, genotype 4 in Southwest Asia, genotype 5 in South Africa and genotype 6 in Indonesia. The aim of this study was to determine the frequency and genotypic distribution of GBV-C in the Colombian population. Methods: Two groups were analyzed: i) 408 Colombian blood donors infected with HCV (n = 250) and HBV (n = 158) from Bogota and ii) 99 indigenous people with HBV infection from Leticia, Amazonas. A fragment of 344 bp from the 5' untranslated region (5' UTR) was amplified by nested RT PCR. Viral sequences were genotyped by phylogenetic analysis using reference sequences from each genotype obtained from GenBank (n = 160). Bayesian phylogenetic analyses were conducted using Markov chain Monte Carlo (MCMC) approach to obtain the MCC tree using BEAST v. 1.5.3. Results: Among blood donors, from 158 HBsAg positive samples, eight 5.06% (n = 8) were positive for GBV-C and from 250 anti-HCV positive samples, 3.2%(n = 8) were positive for GBV-C. Also, 7.7% (n = 7) GBV-C positive samples were found among indigenous people from Leticia. A phylogenetic analysis revealed the presence of the following GBV-C genotypes among blood donors: 2a (41.6%), 1 (33.3%), 3 (16.6%) and 2b (8.3%). All genotype 1 sequences were found in co-infection with HBV and 4/5 sequences genotype 2a were found in co-infection with HCV. All sequences from indigenous people from Leticia were classified as genotype 3. The presence of GBV-C infection was not correlated with the sex (p = 0.43), age (p = 0.38) or origin (p = 0.17). Conclusions: It was found a high frequency of GBV-C genotype 1 and 2 in blood donors. The presence of genotype 3 in indigenous population was previously reported from Santa Marta region in Colombia and in native people from Venezuela and Bolivia. This fact may be correlated to the ancient movements of Asian people to South America a long time ago.

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The attenuation of. mesons in cold nuclear matter has been investigated via the time-dependent multiple-scattering Monte Carlo multicollisional (MCMC) intranuclear cascade model. The inelastic. width deduced from CBELSA/TAPS Collaboration data of meson transparency in complex nuclei (Gamma* similar or equal to 30 MeV/c(2)) is approximately 5 times lower than the value obtained with recent theoretical models and consistent with an in-medium total omega N cross section within 25-30 mb for an average meson momentum of 1.1 GeV/c. The momentum-dependent transparency ratios suggest an elastic/total cross-section ratio around 40%. For the case of CLAS Collaboration data a much higher width is deduced (Gamma* greater than or similar to 120 MeV/c(2)), with the MCMC model providing a consistent interpretation of the data, assuming a much higher meson absorption (sigma(omega N)* greater than or similar to 100 mb) for p(omega) similar to 1.7 GeV/c.

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The mechanism of incoherent pi(0) and eta photoproduction from complex nuclei is investigated from 4 to 12 GeV with an extended version of the multicollisional Monte Carlo (MCMC) intranuclear cascade model. The calculations take into account the elementary photoproduction amplitudes via a Regge model and the nuclear effects of photon shadowing, Pauli blocking, and meson-nucleus final-state interactions. The results for pi(0) photoproduction reproduced for the first time the magnitude and energy dependence of the measured rations sigma(gamma A)/sigma(gamma N) for several nuclei (Be, C, Al, Cu, Ag, and Pb) from a Cornell experiment. The results for eta photoproduction fitted the inelastic background in Cornell's yields remarkably well, which is clearly not isotropic as previously considered in Cornell's analysis. With this constraint for the background, the eta -> gamma gamma. decay width was extracted using the Primakoff method, combining Be and Cu data [Gamma(eta ->gamma gamma) = 0.476(62) keV] and using Be data only [Gamma(eta ->gamma gamma) = 0.512(90) keV]; where the errors are only statistical. These results are in sharp contrast (similar to 50-60%) with the value reported by the Cornell group [Gamma(eta ->gamma gamma). = 0.324(46) keV] and in line with the Particle Data Group average of 0.510(26) keV.

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Hepatitis B is a worldwide health problem affecting about 2 billion people and more than 350 million are chronic carriers of the virus. Nine HBV genotypes (A to I) have been described. The geographical distribution of HBV genotypes is not completely understood due to the limited number of samples from some parts of the world. One such example is Colombia, in which few studies have described the HBV genotypes. In this study, we characterized HBV genotypes in 143 HBsAg-positive volunteer blood donors from Colombia. A fragment of 1306 bp partially comprising HBsAg and the DNA polymerase coding regions (S/POL) was amplified and sequenced. Bayesian phylogenetic analyses were conducted using the Markov Chain Monte Carlo (MCMC) approach to obtain the maximum clade credibility (MCC) tree using BEAST v.1.5.3. Of all samples, 68 were positive and 52 were successfully sequenced. Genotype F was the most prevalent in this population (77%) - subgenotypes F3 (75%) and Fib (2%). Genotype G (7.7%) and subgenotype A2 (15.3%) were also found. Genotype G sequence analysis suggests distinct introductions of this genotype in the country. Furthermore, we estimated the time of the most recent common ancestor (TMRCA) for each HBV/F subgenotype and also for Colombian F3 sequences using two different datasets: (i) 77 sequences comprising 1306 bp of S/POL region and (ii) 283 sequences comprising 681 bp of S/POL region. We also used two other previously estimated evolutionary rates: (i) 2.60 x 10(-4) s/s/y and (ii) 1.5 x 10(-5) s/s/y. Here we report the HBV genotypes circulating in Colombia and estimated the TMRCA for the four different subgenotypes of genotype F. (C) 2010 Elsevier B.V. All rights reserved.

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Molecular epidemiological data concerning the hepatitis B virus (HBV) in Chile are not known completely. Since the HBV genotype F is the most prevalent in the country, the goal of this study was to obtain full HBV genome sequences from patients infected chronically in order to determine their subgenotypes and the occurrence of resistance-associated mutations. Twenty-one serum samples from antiviral drug-naive patients with chronic hepatitis B were subjected to full-length PCR amplification, and both strands of the whole genomes were fully sequenced. Phylogenetic analyses were performed along with reference sequences available from GenBank (n = 290). The sequences were aligned using Clustal X and edited in the SE-AL software. Bayesian phylogenetic analyses were conducted by Markov Chain Monte Carlo simulations (MCMC) for 10 million generations in order to obtain the substitution tree using BEAST. The sequences were also analyzed for the presence of primary drug resistance mutations using CodonCode Aligner Software. The phylogenetic analyses indicated that all sequences were found to be the HBV subgenotype F1b, clustered into four different groups, suggesting that diverse lineages of this subgenotype may be circulating within this population of Chilean patients. J. Med. Virol. 83: 1530-1536, 2011. (C) 2011 Wiley-Liss, Inc.

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Sensitivity and specificity are measures that allow us to evaluate the performance of a diagnostic test. In practice, it is common to have situations where a proportion of selected individuals cannot have the real state of the disease verified, since the verification could be an invasive procedure, as occurs with biopsy. This happens, as a special case, in the diagnosis of prostate cancer, or in any other situation related to risks, that is, not practicable, nor ethical, or in situations with high cost. For this case, it is common to use diagnostic tests based only on the information of verified individuals. This procedure can lead to biased results or workup bias. In this paper, we introduce a Bayesian approach to estimate the sensitivity and the specificity for two diagnostic tests considering verified and unverified individuals, a result that generalizes the usual situation based on only one diagnostic test.

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In this article, we present a generalization of the Bayesian methodology introduced by Cepeda and Gamerman (2001) for modeling variance heterogeneity in normal regression models where we have orthogonality between mean and variance parameters to the general case considering both linear and highly nonlinear regression models. Under the Bayesian paradigm, we use MCMC methods to simulate samples for the joint posterior distribution. We illustrate this algorithm considering a simulated data set and also considering a real data set related to school attendance rate for children in Colombia. Finally, we present some extensions of the proposed MCMC algorithm.

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In this paper, we introduce a Bayesian analysis for survival multivariate data in the presence of a covariate vector and censored observations. Different ""frailties"" or latent variables are considered to capture the correlation among the survival times for the same individual. We assume Weibull or generalized Gamma distributions considering right censored lifetime data. We develop the Bayesian analysis using Markov Chain Monte Carlo (MCMC) methods.

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In this paper, we introduce a Bayesian analysis for bioequivalence data assuming multivariate pharmacokinetic measures. With the introduction of correlation parameters between the pharmacokinetic measures or between the random effects in the bioequivalence models, we observe a good improvement in the bioequivalence results. These results are of great practical interest since they can yield higher accuracy and reliability for the bioequivalence tests, usually assumed by regulatory offices. An example is introduced to illustrate the proposed methodology by comparing the usual univariate bioequivalence methods with multivariate bioequivalence. We also consider some usual existing discrimination Bayesian methods to choose the best model to be used in bioequivalence studies.

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In this paper we make use of some stochastic volatility models to analyse the behaviour of a weekly ozone average measurements series. The models considered here have been used previously in problems related to financial time series. Two models are considered and their parameters are estimated using a Bayesian approach based on Markov chain Monte Carlo (MCMC) methods. Both models are applied to the data provided by the monitoring network of the Metropolitan Area of Mexico City. The selection of the best model for that specific data set is performed using the Deviance Information Criterion and the Conditional Predictive Ordinate method.

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In this paper we deal with a Bayesian analysis for right-censored survival data suitable for populations with a cure rate. We consider a cure rate model based on the negative binomial distribution, encompassing as a special case the promotion time cure model. Bayesian analysis is based on Markov chain Monte Carlo (MCMC) methods. We also present some discussion on model selection and an illustration with a real dataset.