20 found
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  1.  23
    Can a Significance Test Be Genuinely Bayesian?Julio Michael Stern, Carlos Alberto de Braganca Pereira & Sergio Wechsler - 2008 - Bayesian Analysis 3 (1):79-100.
    The Full Bayesian Significance Test, FBST, is extensively reviewed. Its test statistic, a genuine Bayesian measure of evidence, is discussed in detail. Its behavior in some problems of statistical inference like testing for independence in contingency tables is discussed.
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  2.  28
    Bayesian Test of Significance for Conditional Independence: The Multinomial Model.Julio Michael Stern, Pablo de Morais Andrade & Carlos Alberto de Braganca Pereira - 2014 - Entropy 16:1376-1395.
    Conditional independence tests have received special attention lately in machine learning and computational intelligence related literature as an important indicator of the relationship among the variables used by their models. In the field of probabilistic graphical models, which includes Bayesian network models, conditional independence tests are especially important for the task of learning the probabilistic graphical model structure from data. In this paper, we propose the full Bayesian significance test for tests of conditional independence for discrete datasets. The full Bayesian (...)
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  3.  13
    A Straightforward Multiallelic Significance Test for the Hardy-Weinberg Equilibrium Law.Julio Michael Stern, Marcelo de Souza Lauretto, Fabio Nakano, Silvio Rodrigues Faria & Carlos Alberto de Braganca Pereira - 2009 - Genetics and Molecular Biology 32 (3):619-625.
    Much forensic inference based upon DNA evidence is made assuming Hardy-Weinberg Equilibrium (HWE) for the genetic loci being used. Several statistical tests to detect and measure deviation from HWE have been devised, and their limitations become more obvious when testing for deviation within multiallelic DNA loci. The most popular methods-Chi-square and Likelihood-ratio tests-are based on asymptotic results and cannot guarantee a good performance in the presence of low frequency genotypes. Since the parameter space dimension increases at a quadratic rate on (...)
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  4.  7
    Full Bayesian Significance Test Applied to Multivariate Normal Structure Models.Marcelo de Souza Lauretto, Carlos Alberto de Braganca Pereira, Julio Michael Stern & Shelemiahu Zacks - 2003 - Brazilian Journal of Probability and Statistics 17:147-168.
    Abstract: The Pull Bayesian Significance Test (FBST) for precise hy- potheses is applied to a Multivariate Normal Structure (MNS) model. In the FBST we compute the evidence against the precise hypothesis. This evi- dence is the probability of the Highest Relative Surprise Set (HRSS) tangent to the sub-manifold (of the parameter space) that defines the null hypothesis. The MNS model we present appears when testing equivalence conditions for genetic expression measurements, using micro-array technology.
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  5.  13
    Evidence and Credibility: Full Bayesian Significance Test for Precise Hypotheses.Julio Michael Stern & Carlos Alberto de Braganca Pereira - 1999 - Entropy 1 (1):69-80.
    A Bayesian measure of evidence for precise hypotheses is presented. The intention is to give a Bayesian alternative to significance tests or, equivalently, to p-values. In fact, a set is defined in the parameter space and the posterior probability, its credibility, is evaluated. This set is the “Highest Posterior Density Region” that is “tangent” to the set that defines the null hypothesis. Our measure of evidence is the complement of the credibility of the “tangent” region.
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  6.  17
    Actuarial Analysis Via Branching Processes.Julio Michael Stern & Carlos Alberto de Braganca Pereira - 2000 - Annals of the 6th ISAS-SCI 8:353-358.
    We describe a software system for the analysis of defined benefit actuarial plans. The system uses a recursive formulation of the actuarial stochastic processes to implement precise and efficient computations of individual and group cash flows.
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  7.  26
    A Dynamic Software Certification and Verification Procedure.Julio Michael Stern & Carlos Alberto de Braganca Pereira - 1998 - SCI’99 Proceedings 2:426-435.
    in Oct-14-1998 ordinance INDESP-IO4 established the federal software certification and verification requirements for gaming machines in Brazil. The authors present the rationale behind these criteria, whose basic principles can find applications in several other software authentication applications.
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  8.  26
    A Weibull Wearout Test: Full Bayesian Approach.Julio Michael Stern, Telba Zalkind Irony, Marcelo de Souza Lauretto & Carlos Alberto de Braganca Pereira - 2001 - Reliability and Engineering Statistics 5:287-300.
    The Full Bayesian Significance Test (FBST) for precise hypotheses is presented, with some applications relevant to reliability theory. The FBST is an alternative to significance tests or, equivalently, to p-ualue.s. In the FBST we compute the evidence of the precise hypothesis. This evidence is the probability of the complement of a credible set "tangent" to the sub-manifold (of the para,rreter space) that defines the null hypothesis. We use the FBST in an application requiring a quality control of used components, based (...)
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  9.  8
    Cointegration: Bayesian Significance Test Communications in Statistics.Julio Michael Stern, Marcio Alves Diniz & Carlos Alberto de Braganca Pereira - 2012 - Communications in Statistics 41 (19):3562-3574.
    To estimate causal relationships, time series econometricians must be aware of spurious correlation, a problem first mentioned by Yule (1926). To deal with this problem, one can work either with differenced series or multivariate models: VAR (VEC or VECM) models. These models usually include at least one cointegration relation. Although the Bayesian literature on VAR/VEC is quite advanced, Bauwens et al. (1999) highlighted that “the topic of selecting the cointegrating rank has not yet given very useful and convincing results”. The (...)
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  10.  16
    Combining Optimization and Randomization Approaches for the Design of Clinical Trials.Julio Michael Stern, Victor Fossaluza, Marcelo de Souza Lauretto & Carlos Alberto de Braganca Pereira - 2015 - Springer Proceedings in Mathematics and Statistics 118:173-184.
    t Intentional sampling methods are non-randomized procedures that select a group of individuals for a sample with the purpose of meeting specific prescribed criteria. In this paper we extend previous works related to intentional sampling, and address the problem of sequential allocation for clinical trials with few patients. Roughly speaking, patients are enrolled sequentially, according to the order in which they start the treatment at the clinic or hospital. The allocation problem consists in assigning each new patient to one, and (...)
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  11.  10
    Enviromental Genotoxicity Evaluation: Bayesian Approach for a Mixture Statistical Model.Julio Michael Stern, Angela Maria de Souza Bueno, Carlos Alberto de Braganca Pereira & Maria Nazareth Rabello-Gay - 2002 - Stochastic Environmental Research and Risk Assessment 16:267–278.
    The data analyzed in this paper are part of the results described in Bueno et al. (2000). Three cytogenetics endpoints were analyzed in three populations of a species of wild rodent – Akodon montensis – living in an industrial, an agricultural, and a preservation area at the Itajaí Valley, State of Santa Catarina, Brazil. The polychromatic/normochromatic ratio, the mitotic index, and the frequency of micronucleated polychromatic erythrocites were used in an attempt to establish a genotoxic profile of each area. It (...)
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  12.  8
    FBST Regularization and Model Selection.Julio Michael Stern & Carlos Alberto de Braganca Pereira - 2001 - In Annals of the 7th International Conference on Information Systems Analysis and Synthesis. Orlando FL: pp. 7: 60-65..
    We show how the Full Bayesian Significance Test (FBST) can be used as a model selection criterion. The FBST was presented by Pereira and Stern as a coherent Bayesian significance test. Key Words: Bayesian test; Evidence; Global optimization; Information; Model selection; Numerical integration; Posterior density; Precise hypothesis; Regularization. AMS: 62A15; 62F15; 62H15.
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  13.  10
    Genuine Bayesian Multiallelic Significance Test for the Hardy-Weinberg Equilibrium Law.Julio Michael Stern, Carlos Alberto de Braganca Pereira, Fabio Nakano & Martin Ritter Whittle - 2006 - Genetics and Molecular Research 5 (4):619-631.
    Statistical tests that detect and measure deviation from the Hardy-Weinberg equilibrium (HWE) have been devised but are limited when testing for deviation at multiallelic DNA loci is attempted. Here we present the full Bayesian significance test (FBST) for the HWE. This test depends neither on asymptotic results nor on the number of possible alleles for the particular locus being evaluated. The FBST is based on the computation of an evidence index in favor of the HWE hypothesis. A great deal of (...)
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  14.  9
    Hierarchical Forecasting with Polynomial Nets.Julio Michael Stern, Fabio Nakano, Marcelo de Souza Lauretto & Carlos Alberto de Braganca Pereira - 2009 - Studies in Computational Intelligence 199:305-315.
    This article presents a two level hierarchical forecasting model developed in a consulting project for a Brazilian magazine publishing company. The first level uses a VARMA model and considers econometric variables. The second level takes into account qualitative aspects of each publication issue, and is based on polynomial networks generated by Genetic Programming (GP).
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  15.  16
    Intentional Sampling by Goal Optimization with Decoupling by Stochastic Perturbation.Julio Michael Stern, Marcelo de Souza Lauretto, Fabio Nakano & Carlos Alberto de Braganca Pereira - 2012 - AIP Conference Proceedings 1490:189-201.
    Intentional sampling methods are non-probabilistic procedures that select a group of individuals for a sample with the purpose of meeting specific prescribed criteria. Intentional sampling methods are intended for exploratory research or pilot studies where tight budget constraints preclude the use of traditional randomized representative sampling. The possibility of subsequently generalize statistically from such deterministic samples to the general population has been the issue of long standing arguments and debates. Nevertheless, the intentional sampling techniques developed in this paper explore pragmatic (...)
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  16.  7
    Special Characterizations of Standard Discrete Models.Julio Michael Stern & Carlos Alberto de Braganca Pereira - 2008 - RevStat – Statistical Journal 6:199-230.
    This article presents important properties of standard discrete distributions and its conjugate densities. The Bernoulli and Poisson processes are described as generators of such discrete models. A characterization of distributions by mixtures is also introduced. This article adopts a novel singular notation and representation. Singular representations are unusual in statistical texts. Nevertheless, the singular notation makes it simpler to extend and generalize theoretical results and greatly facilitates numerical and computational implementation.
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  17.  14
    The Full Bayesian Significance Test for Mixture Models: Results in Gene Expression Clustering.Julio Michael Stern, Marcelo de Souza Lauretto & Carlos Alberto de Braganca Pereira - 2008 - Genetics and Molecular Research 7 (3):883-897.
    Gene clustering is a useful exploratory technique to group together genes with similar expression levels under distinct cell cycle phases or distinct conditions. It helps the biologist to identify potentially meaningful relationships between genes. In this study, we propose a clustering method based on multivariate normal mixture models, where the number of clusters is predicted via sequential hypothesis tests: at each step, the method considers a mixture model of m components (m = 2 in the first step) and tests if (...)
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  18.  10
    The Problem of Separate Hypotheses Via Mixtures Models.Julio Michael Stern, Marcelo de Souza Lauretto, Silvio Rodrigues Faria & Carlos Alberto de Braganca Pereira - 2007 - AIP Conference Proceedings 954:268-275.
    This article describes the Full Bayesian Significance Test for the problem of separate hypotheses. Numerical experiments are performed for the Gompertz vs. Weibull life span test.
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  19.  17
    TORC3: Token-Ring Clearing Heuristic for Currency Circulation.Julio Michael Stern, Carlos Humes, Marcelo de Souza Lauretto, Fabio Nakano, Carlos Alberto de Braganca Pereira & Guilherme Frederico Gazineu Rafare - 2012 - AIP Conference Proceedings 1490:179-188.
    Clearing algorithms are at the core of modern payment systems, facilitating the settling of multilateral credit messages with (near) minimum transfers of currency. Traditional clearing procedures use batch processing based on MILP - mixed-integer linear programming algorithms. The MILP approach demands intensive computational resources; moreover, it is also vulnerable to operational risks generated by possible defaults during the inter-batch period. This paper presents TORC3 - the Token-Ring Clearing Algorithm for Currency Circulation. In contrast to the MILP approach, TORC3 is a (...)
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  20.  11
    Unit Roots: Bayesian Significance Test.Julio Michael Stern, Marcio Alves Diniz & Carlos Alberto de Braganca Pereira - 2011 - Communications in Statistics 40 (23):4200-4213.
    The unit root problem plays a central role in empirical applications in the time series econometric literature. However, significance tests developed under the frequentist tradition present various conceptual problems that jeopardize the power of these tests, especially for small samples. Bayesian alternatives, although having interesting interpretations and being precisely defined, experience problems due to the fact that that the hypothesis of interest in this case is sharp or precise. The Bayesian significance test used in this article, for the unit root (...)
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