Bayesian Implementation
Mostrando 1-12 de 17 artigos, teses e dissertações.
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1. Modeling Bayesian Networks from a conceptual framework for occupational risk analysis
Abstract Occupational risk is the possibility that some element included in a particular work environment can cause damage to someone’s health. Thereby, the risk is understood as the product of probability and consequences. In this sense, risk analysis through probabilistic stochastic techniques, such as Bayesian networks (BN), becomes an important tool to
Prod.. Publicado em: 20/07/2017
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2. ANN model of RF MEMS Lateral SPDT switches for millimeter wave applications
This paper presents Artificial Neural Network (ANN) implementation for the Radio Frequency (RF) and Mechanical modeling of lateral RF Micro Electro Mechanical System (MEMS) series micro machined Single pole double through (SPDT) switch. We propose an efficient approach based on ANN for analyzing the losses in ON and OFF state of lateral RF MEMS series switch
Journal of Microwaves, Optoelectronics and Electromagnetic Applications. Publicado em: 2012-06
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3. Enriching Information to Prevent Bank Runs
Sequential service in the banking sector, as modeled by Diamond and Dybvig (1983), is a barrier to full insurance and potential source of financial fragility against which deposit insurance is infeasible (Wallace, 1988). In this paper, we pursue a different perspective, viewing the sequence of contacts as opportunities to extract information through a larger
Escola de Pós-Graduação em Economia da FGV. Publicado em: 27/07/2011
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4. Skew normal mixed models in microarray data generated from complex pedigrees / Modelos mistos normais assimÃtricos em dados de microarrays originados de pedigrees complexos / Modelos mistos normais assimÃtricos em dados de microarrays originados de pedigrees complexos / Skew normal mixed models in microarray data generated from complex pedigrees
Estimates of heritability for gene expression are scarce and commonly originated from family structures, in which the variability of responses among and within families are provided under a uniform covariance structure for related individuals, ignoring the known relationship among all individuals in the pedigree. Gauss-Markov normal mixed models are the usua
Publicado em: 2009
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5. Modelos de regressão logística clássica, Bayesiana e redes neurais para Credit Scoring
Important advances have been achieved in the granting of credit, however, the problem of identifying good customers for the granting of credit does not provide a definitive solution. Several techniques were presented and are being developed, each presents its characteristics, advantages and disadvantages as to their discrimination power, robustness, ease of
Publicado em: 2008
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6. Um novo modelo para cálculo de probabilidade de paternidade - concepção e implementação / A Novel Model for Paternity Probability Calculation - Design and Implementation
Nesta tese são apresentados um novo modelo estatístico para cálculo de probabilidade de paternidade e sua implementação em software. O modelo proposto utiliza o genótipo como informação básica, em contraste com outros modelos que usam alelos. Por esta diferença, o modelo proposto resulta mais abrangente, mas que, sob certas restrições, reproduz o
Publicado em: 2006
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7. Monte Carlo methods in nonlinear filtering theory.
This thesis is focused on two basic aspects of the Control Problem: the stochastic modelling of physical systems, and Monte Carlo-based numerical approximation of the nonlinear filtering problem solution. In the first topic this thesis concerns about clarifying some issues in the mathematical modeling of continuous-time systems with Brownian motion. The hypo
Publicado em: 2006
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8. Métodos atuariais aplicados à determinação da taxa de prêmio de contratos de seguro agrícola: um estudo de caso. / Actuarial methods applied to the determination of the premium rate of crop insurance contracts: a case study.
This research analyses alternative methods of pricing agricultural insurance contract based on regional yields. The premium rate is calculated using three different approaches: nonparametric method to estimate the density of the agricultural yield; parametric approach fitting the Normal and Beta distributions; and, hierarchical Bayesian models. The data gene
Publicado em: 2005
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9. Virtual.Prob - Ambiente virtual para auxÃlio e verificaÃÃo do aprendizado
This work presents a virtual learning environment, Virtual.Prob, whose objective is to help the student to study Probability in the discipline Statistics and Probability for Computing (ET 586). This discipline is part of the Computer Engineering and Computer Science courses at UFPE. Virtual.Prob is based on the machine learning technique known as Bayesian Ne
Publicado em: 2004
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10. MODELO BAYESIANO PARA ESTIMAÇÃO DO NÍVEL DE LEMBRANÇA DE PROPAGANDA EM MARKETING / BAYESIAN MODEL TO ESTIMATE ADVERTISING RECALL IN MARKETING
Analysis of consumer markets define and attempt to measure many variables in studies of the effectiveness of adversitising. The awareness in a consumer population of a particular advertising is one such quantity, the subject of the above-referenced studies. We define and give the implementation of model based in dynamic Generalised Linear Models which is use
Publicado em: 1997
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11. LINEAR GROWTH BAYESIAN MODEL USING DISCOUNT FACTORS / MODELO BAYESIANO DE CRESCIMENTO LINEAR COM DESCONTOS
The aim of this thesis is to discuss in details the Multiprocess Linear Grawth Bayesian Model for seasonal and/or nonseasonal series, using discount factors. The original formulation of this model was put forward recently by Ameen and Harrison. In the first part of the thesis (chapters 2 and 3) we show some general concepts related to time series and time se
Publicado em: 1985
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12. Dimensional reduction for a Bayesian filter
An adaptive strategy is proposed for reducing the number of unknowns in the calculation of a proposal distribution in a sequential Monte Carlo implementation of a Bayesian filter for nonlinear dynamics. The idea is to solve only in directions in which the dynamics is expanding, found adaptively; this strategy is suggested by earlier work on optimal predictio
National Academy of Sciences.