951 resultados para Conjugate Prior
Resumo:
In mathematical modeling the estimation of the model parameters is one of the most common problems. The goal is to seek parameters that fit to the measurements as well as possible. There is always error in the measurements which implies uncertainty to the model estimates. In Bayesian statistics all the unknown quantities are presented as probability distributions. If there is knowledge about parameters beforehand, it can be formulated as a prior distribution. The Bays’ rule combines the prior and the measurements to posterior distribution. Mathematical models are typically nonlinear, to produce statistics for them requires efficient sampling algorithms. In this thesis both Metropolis-Hastings (MH), Adaptive Metropolis (AM) algorithms and Gibbs sampling are introduced. In the thesis different ways to present prior distributions are introduced. The main issue is in the measurement error estimation and how to obtain prior knowledge for variance or covariance. Variance and covariance sampling is combined with the algorithms above. The examples of the hyperprior models are applied to estimation of model parameters and error in an outlier case.
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We complete the development of a testing ground for axioms of discrete stochastic choice. Our contribution here is to develop new posterior simulation methods for Bayesian inference, suitable for a class of prior distributions introduced by McCausland and Marley (2013). These prior distributions are joint distributions over various choice distributions over choice sets of di fferent sizes. Since choice distributions over di fferent choice sets can be mutually dependent, previous methods relying on conjugate prior distributions do not apply. We demonstrate by analyzing data from a previously reported experiment and report evidence for and against various axioms.
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This study proposes to ascertain the importance of each alimentary category in the Tetrapturus albidus diet composition, as well as to propose the use of the Bayesian approach for analysis of these data. The stomachs were collected during fishing cruises carried out by the Santos-SP longliner from July 2007 to June 2008. For Bayesian model formulation, each alimentary item was clustered in four food categories as: teleost, cephalopod, crustaceans, and others. To estimate the proportion of each food category, the multinomial model with Dirichlet conjugate prior distribution was used. After the stomach contents analysis, 133 food items were identified, which belonged to 9 taxa. The most important food category is constituted by cephalopod molluscs, followed by teleost fishes. The food category comprised of crustaceans presents a low contribution and in this case it could be considered to be an accidental food item. The Bayesian approach means a distinct view in relation to traditional methods, as it permits one to incorporate information obtained from the literature. It should be useful to analyse great top predators, which are usually caught in small numbers.
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The Dirichlet distribution is a multivariate generalization of the Beta distribution. It is an important multivariate continuous distribution in probability and statistics. In this report, we review the Dirichlet distribution and study its properties, including statistical and information-theoretic quantities involving this distribution. Also, relationships between the Dirichlet distribution and other distributions are discussed. There are some different ways to think about generating random variables with a Dirichlet distribution. The stick-breaking approach and the Pólya urn method are discussed. In Bayesian statistics, the Dirichlet distribution and the generalized Dirichlet distribution can both be a conjugate prior for the Multinomial distribution. The Dirichlet distribution has many applications in different fields. We focus on the unsupervised learning of a finite mixture model based on the Dirichlet distribution. The Initialization Algorithm and Dirichlet Mixture Estimation Algorithm are both reviewed for estimating the parameters of a Dirichlet mixture. Three experimental results are shown for the estimation of artificial histograms, summarization of image databases and human skin detection.
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Understanding how virus strains offer protection against closely related emerging strains is vital for creating effective vaccines. For many viruses, including Foot-and-Mouth Disease Virus (FMDV) and the Influenza virus where multiple serotypes often co-circulate, in vitro testing of large numbers of vaccines can be infeasible. Therefore the development of an in silico predictor of cross-protection between strains is important to help optimise vaccine choice. Vaccines will offer cross-protection against closely related strains, but not against those that are antigenically distinct. To be able to predict cross-protection we must understand the antigenic variability within a virus serotype, distinct lineages of a virus, and identify the antigenic residues and evolutionary changes that cause the variability. In this thesis we present a family of sparse hierarchical Bayesian models for detecting relevant antigenic sites in virus evolution (SABRE), as well as an extended version of the method, the extended SABRE (eSABRE) method, which better takes into account the data collection process. The SABRE methods are a family of sparse Bayesian hierarchical models that use spike and slab priors to identify sites in the viral protein which are important for the neutralisation of the virus. In this thesis we demonstrate how the SABRE methods can be used to identify antigenic residues within different serotypes and show how the SABRE method outperforms established methods, mixed-effects models based on forward variable selection or l1 regularisation, on both synthetic and viral datasets. In addition we also test a number of different versions of the SABRE method, compare conjugate and semi-conjugate prior specifications and an alternative to the spike and slab prior; the binary mask model. We also propose novel proposal mechanisms for the Markov chain Monte Carlo (MCMC) simulations, which improve mixing and convergence over that of the established component-wise Gibbs sampler. The SABRE method is then applied to datasets from FMDV and the Influenza virus in order to identify a number of known antigenic residue and to provide hypotheses of other potentially antigenic residues. We also demonstrate how the SABRE methods can be used to create accurate predictions of the important evolutionary changes of the FMDV serotypes. In this thesis we provide an extended version of the SABRE method, the eSABRE method, based on a latent variable model. The eSABRE method takes further into account the structure of the datasets for FMDV and the Influenza virus through the latent variable model and gives an improvement in the modelling of the error. We show how the eSABRE method outperforms the SABRE methods in simulation studies and propose a new information criterion for selecting the random effects factors that should be included in the eSABRE method; block integrated Widely Applicable Information Criterion (biWAIC). We demonstrate how biWAIC performs equally to two other methods for selecting the random effects factors and combine it with the eSABRE method to apply it to two large Influenza datasets. Inference in these large datasets is computationally infeasible with the SABRE methods, but as a result of the improved structure of the likelihood, we are able to show how the eSABRE method offers a computational improvement, leading it to be used on these datasets. The results of the eSABRE method show that we can use the method in a fully automatic manner to identify a large number of antigenic residues on a variety of the antigenic sites of two Influenza serotypes, as well as making predictions of a number of nearby sites that may also be antigenic and are worthy of further experiment investigation.
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In this work, we present the solution of a class of linear inverse heat conduction problems for the estimation of unknown heat source terms, with no prior information of the functional forms of timewise and spatial dependence of the source strength, using the conjugate gradient method with an adjoint problem. After describing the mathematical formulation of a general direct problem and the procedure for the solution of the inverse problem, we show applications to three transient heat transfer problems: a one-dimensional cylindrical problem; a two-dimensional cylindrical problem; and a one-dimensional problem with two plates.
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The aim of this study was to investigate the possible effects of reproductive experience on dopaminergic profile in three different brain tissues, hypothalamus, striatum and cortex in rats on 7th-8th day of pregnancy during the light-dark shift (between 1700-1900h). Results showed that in hypothalamus, dopamine levels increased and DOPAC/DA decreased as a function of parity. In cortex, no differences were observed. In striata, the haloperidol-induced HVA and HVA/DA increases were less intense in experienced animals. These findings suggested that reproductive experience produced functional central changes during pregnancy, with different neurochemical responses depending on the brain region.
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A multi-pumping flow system exploiting prior assay is proposed for sequential turbidimetric determination of sulphate and chloride in natural waters. Both methods are implemented in the same manifold that provides facilities for: in-line sample clean-up with a Bio-Rex 70 mini-column with fluidized beads: addition of low amounts of sulphate or chloride ions to the reaction medium for improving supersaturation; analyte precipitation with Ba(2+) or Ag(+); real-time decision on the need for next assay. The sample is initially run for chloride determination, and the analytical signal is compared with a preset value. If higher, the sample is run again, now for sulphate determination. The strategy may lead to all increased sample throughput. The proposed system is computer-controlled and presents enhanced figures of merit. About 10 samples are run per hour (about 60 measurements) and results are reproducible and Unaffected by the presence of potential interfering ions at concentration levels usually found in natural waters. Accuracy was assessed against ion chromatography. (C) 2008 Elsevier B.V. All rights reserved.
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A method for the determination of artemether (ART) and its main metabolite dihydroartemisinin (DHA) in plasma employing liquid-phase microextraction (LPME) for sample preparation prior to liquid chromatography-tandem mass spectrometry (LC-MS-MS) was developed. The analytes were extracted from 1 nil, of plasma utilizing a two-phase LPME procedure with artemisinin as internal standard. Using the optimized LPME conditions, mean absolute recovery rates of 25 and 32% for DHA and ART, respectively, were achieved using toluene-n-octanol (1:1, viv) as organic phase with an extraction time of 30 min. After extraction, the analytes were resolved within 5 min using a mobile phase consisting of methanol-ammonium acetate (10 mmol L(-1) pH 5.0, 80:20. v/v) on a laboratory-made column based on poly(methyltetradecylsiloxane) attached to a zirconized-silica support. MS-MS detection was employed using an electrospray interface in the positive ion mode. The method developed was linear over the range of 5-1000 ng mL(-1) for both analytes. Precision and accuracy were within acceptable levels of confidence (<15%). The assay was applied to the determination of these analytes in plasma from rats treated with ART. The two-phase LPME procedure is affordable and the solvent consumption was very low compared to the traditional methods of sample preparation. (C) 2010 Elsevier B.V. All rights reserved.
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DHEA, a steroid hormone synthesized from cholesterol by cells of the adrenal cortex, plays an essential role in enhancing the host`s resistance to different experimental infections. Receptors for this hormone can be found in distinct immune cells (especially macrophages) that are known to be the first line defense against Trypanosoma cruzi infection. These cells operate through an indirect pathway releasing nitric oxide (NO) and cytokines such TNF-alpha and IL-12 which in turn trigger an enhancement of natural killer cells and lymphocytes which finally secrete pro and anti-inflammatory cytokines. The effects of pre- and post-infection DHEA treatment on production of IL-12, TNF alpha and NO were evaluated. T. cruzi infected macrophages post treated with DHEA displayed enhanced concentrations of TNF-alpha, IL-12 and NO. Probably, the mechanisms that induced the production of cytokines by infected cells are more efficient when the immune system has been stimulated first by parasite invasion, suggesting that the protective role of DHEA is greater when administered post infection. (C) 2011 Elsevier B.V. All rights reserved.
Resumo:
There is concern over the safety of calcium channel blockers (CCBs) in acute coronary disease. We sought to determine if patients taking calcium channel blockers (CCBs) at the time of admission with acute myocardial infarction (AMI) had a higher case-fatality compared with those taking beta-blockers or neither medication. Clinical and drug treatment variables at the time of hospital admission predictive of survival at 28 days were examined in a community-based registry of patients aged under 65 years admitted to hospital for suspected AMI in Perth, Australia, between 1984 and 1993. Among 7766 patients, 1291 (16.6%) were taking a CCB and 1259 (16.2%) a betablocker alone at hospital admission. Patients taking CCBs had a worse clinical profile than those taking a beta-blocker alone or neither drug (control group), and a higher unadjusted 28-day mortality (17.6% versus 9.3% and 11.1% respectively, both P < 0.001). There was no significant heterogeneity with respect to mortality between nifedipine, diltiazem, or verapamil when used alone, or with a beta-blocker. After adjustment for factors predictive of death at 28 days, patients taking a CCB were found not to have an excess chance of death compared with the control group (odds ratio [OR] 1.06, 95% confidence interval [CI]; 0.87, 1.30), whereas those taking a beta-blocker alone had a lower odds of death (OR 0.75, 95% CI; 0.59, 0.94). These results indicate that established calcium channel blockade is not associated with an excess risk of death following AMI once other differences between patients are taken into account, but neither does it have the survival advantage seen with prior beta-blocker therapy.
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With the purpose of approximating two issues, oral narrative and constructive memory, we assume that children, as well as adults, have a constructive memory. Accordingly, researchers of the constructive memory share with piagetians the vision that memory is an applied cognition. Under this perspective, understanding and coding into memory constitute a process which is considered similar to the piagetian assimilation of building an internal conceptual representation of the information (hence the term constructive memory. The objective of this study is to examine and illustrate, through examples drawn from a research about oral narrative with 5, 8 and 10 years old children, the extent to which the constructive memory is stimulated by the acquisition of the structures of knowledge or ""mental models"" (schemes of stories and scenes, scripts), and if they automatically employ them to process constructively the information in storage and rebuild them in the recovery. A sequence of five pictures from a book without text was transformed into computerized program, and the pictures were thus presented to the children. The story focuses on a misunderstanding of two characters on a different assessment about a key event. In data collection, the demands of memory were preserved, since children narrate their stories when the images were no longer viewed on the computer screen. Each narrative was produced as a monologue. The results show that this story can be told either in a descriptive level or in a more elaborated level, where intentions and beliefs are attributed to the characters. Although this study allows an assessment of the development of children`s capabilities (both cognitive and linguistic) to narrate a story, there are for sure other issues that could be exploited.
Resumo:
Purpose The third-generation nonsteroidal aromatase inhibitors (AIs) are increasingly used as adjuvant and first-line advanced therapy for postmenopausal, hormone receptor-positive (HR +) breast cancer. Because many patients subsequently experience progression or relapse, it is important to identify agents with efficacy after AI failure. Materials and Methods Evaluation of Faslodex versus Exemestane Clinical Trial (EFECT) is a randomized, double-blind, placebo controlled, multicenter phase III trial of fulvestrant versus exemestane in postmenopausal women with HR + advanced breast cancer (ABC) progressing or recurring after nonsteroidal AI. The primary end point was time to progression (TTP). A fulvestrant loading-dose (LD) regimen was used: 500 mg intramuscularly on day 0, 250 mg on days 14, 28, and 250 mg every 28 days thereafter. Exemestane 25 mg orally was administered once daily. Results A total of 693 women were randomly assigned to fulvestrant (n = 351) or exemestane ( n = 342). Approximately 60% of patients had received at least two prior endocrine therapies. Median TTP was 3.7 months in both groups ( hazard ratio = 0.963; 95% CI, 0.819 to 1.133; P = .6531). The overall response rate ( 7.4% v 6.7%; P = .736) and clinical benefit rate ( 32.2% v 31.5%; P = .853) were similar between fulvestrant and exemestane respectively. Median duration of clinical benefit was 9.3 and 8.3 months, respectively. Both treatments were well tolerated, with no significant differences in the incidence of adverse events or quality of life. Pharmacokinetic data confirm that steady-state was reached within 1 month with the LD schedule of fulvestrant. Conclusion Fulvestrant LD and exemestane are equally active and well-tolerated in a meaningful proportion of postmenopausal women with ABC who have experienced progression or recurrence during treatment with a nonsteroidal AI.
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Pneumococcal vaccination has been recommended for immunocompromised children, including patients with chronic kidney disease. We determined pneumococcal immunoglobulin (Ig) G antibodies to serotypes 4, 6B, 9V, 14, 18C, 19F, and 23F before and after 48 pediatric patients with chronic renal failure were administered heptavalent conjugated pneumococcal vaccine. The patients were between 1 and 9 years of age and were separated into a conservative treatment group (Group 1) and a dialysis group Group 2). The antibody response to the vaccinal serotypes was evaluated by measuring antibody concentrations before the first dose and 60 days after the second one. Pre-vaccinal IgG concentrations >= 0.35 mu g/ml were detected for all serotypes in at least 50% of the patients in both groups. Patients from both groups showed a statistically indistinguishable behavior in terms of the medians of post-vaccination IgG levels. An ""adequate"" vaccine response was defined as a post-immunization level of specific pneumococcal serotype antibody >= 0.35 mu g/ml, based on the World Health Organization`s (WHO) protective antibody concentration definition for pneumococcal conjugate vaccines, or on a fourfold increase over baseline for at least five of the seven antigens of the vaccine. An ""adequate"" vaccinal response was obtained in 100% of the patients of both groups using WHO`s definition, or in 45.8% of Group 1 patients and 37.5% of Group 2 patients when the criterion was a fourfold antibody increase over baseline antibody concentrations.