The probability of gas escapes from steel pipelines due to different types of corrosion is studied with real failure data from an urban gas distribution network. Both the design and maintenance of the network are considered, identifying and estimating (in a Bayesian framework) an elementary multinomial model in the first case, and a more sophisticated non-homogeneous Poisson process in the second case. Special attention is paid to the elicitation of the experts' opinions.
View Article and Find Full Text PDFGenerative Bayesian Computation (GBC) methods are developed to provide an efficient computational solution for maximum expected utility (MEU). We propose a density-free generative method based on quantiles that naturally calculates expected utility as a marginal of posterior quantiles. Our approach uses a deep quantile neural estimator to directly simulate distributional utilities.
View Article and Find Full Text PDFIn the last decade, a large amount of data from vehicle location sensors has been generated due to the massification of GPS systems to track them. This is because these sensors usually include multiple variables such as position, speed, angular position of the vehicle, etc., and, furthermore, they are also usually recorded in very short time intervals.
View Article and Find Full Text PDFStoch Environ Res Risk Assess
August 2021
Health care prescription fraud and abuse result in major financial losses and adverse health effects. The growing budget deficits of health insurance programs and recent opioid drug abuse crisis in the United States have accelerated the use of analytical methods. Unsupervised methods such as clustering and anomaly detection could help the health care auditors to evaluate the billing patterns when embedded into rule-based frameworks.
View Article and Find Full Text PDFThe use of expert knowledge to quantify a Bayesian Network (BN) is necessary when data is not available. This however raises questions regarding how opinions from multiple experts can be used in a BN. Linear pooling is a popular method for combining probability assessments from multiple experts.
View Article and Find Full Text PDFContext: Because of the increasing body of literature on neuropathic cancer pain (NCP), an accurate estimate of its prevalence requires recurring updates.
Objectives: To provide this estimate using information from a systematic review and a survey.
Methods: Using MEDLINE, Embase, and a previous review, we searched for studies published up to 2014 reporting data on NCP prevalence in adult cancer populations.
Functional response estimation and population tracking in predator-prey systems are critical problems in ecology. In this paper we consider a stochastic predator-prey system with a Lotka-Volterra functional response and propose a particle filtering method for: (a) estimating the behavioral parameter representing the rate of effective search per predator in the functional response and (b) forecasting the population biomass using field data. In particular, the proposed technique combines a sequential Monte Carlo sampling scheme for tracking the time-varying biomass with the analytical integration of the unknown behavioral parameter.
View Article and Find Full Text PDFPulsatile mock loop systems are largely used to investigate the cardiovascular system in vitro. They consist of a pump, which replicates the heart, coupled with a lumped-parameter hydraulic afterload, which simulates vasculature. An accurate dimensioning of components is required for a reliable mimicking of the physiopathological behavior of the system.
View Article and Find Full Text PDFBiological plausibility and other prior information could help select genome-wide association (GWA) findings for further follow-up, but there is no consensus on which types of knowledge should be considered or how to weight them. We used experts' opinions and empirical evidence to estimate the relative importance of 15 types of information at the single-nucleotide polymorphism (SNP) and gene levels. Opinions were elicited from 10 experts using a two-round Delphi survey.
View Article and Find Full Text PDFPrioritization is the process whereby a set of possible candidate genes or SNPs is ranked so that the most promising can be taken forward into further studies. In a genome-wide association study, prioritization is usually based on the P-values alone, but researchers sometimes take account of external annotation information about the SNPs such as whether the SNP lies close to a good candidate gene. Using external information in this way is inherently subjective and is often not formalized, making the analysis difficult to reproduce.
View Article and Find Full Text PDFParameter estimation for the functional response of predator-prey systems is a critical methodological problem in population ecology. In this paper we consider a stochastic predator-prey system with non-linear Ivlev functional response and propose a method for model parameter estimation based on time series of field data. We tackle the problem of parameter estimation using a Bayesian approach relying on a Markov Chain Monte Carlo algorithm.
View Article and Find Full Text PDFTo ascertain the viability of a project, undertake resource allocation, take part in bidding processes, and other related decisions, modern project management requires forecasting techniques for cost, duration, and performance of a project, not only under normal circumstances, but also under external events that might abruptly change the status quo. We provide a Bayesian framework that provides a global forecast of a project's performance. We aim at predicting the probabilities and impacts of a set of potential scenarios caused by combinations of disruptive events, and using this information to deal with project management issues.
View Article and Find Full Text PDFBull Math Biol
February 2008
We present a Bayesian method for functional response parameter estimation starting from time series of field data on predator-prey dynamics. Population dynamics is described by a system of stochastic differential equations in which behavioral stochasticities are represented by noise terms affecting each population as well as their interaction. We focus on the estimation of a behavioral parameter appearing in the functional response of predator to prey abundance when a small number of observations is available.
View Article and Find Full Text PDFMMVB is a QM/MM hybrid method, consisting of a molecular mechanics force field coupled to a valence bond Heisenberg Hamiltonian parametrized from ab initio CASSCF calculations on several prototype molecules. The Heisenberg Hamiltonian matrix elements Q(ij) and K(ij), whose expressions are partitioned here into a primary contribution and second-order correction terms, are calculated analytically in MMVB. When the original MMVB force field fails to produce potential energy surfaces accurate enough for dynamics calculations, we show that significant improvements can be made by refitting the second-order correction terms for the particular molecule(s) being studied.
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