Search results for "BAYESIAN"
showing 10 items of 604 documents
Forecasting correlated time series with exponential smoothing models
2011
Abstract This paper presents the Bayesian analysis of a general multivariate exponential smoothing model that allows us to forecast time series jointly, subject to correlated random disturbances. The general multivariate model, which can be formulated as a seemingly unrelated regression model, includes the previously studied homogeneous multivariate Holt-Winters’ model as a special case when all of the univariate series share a common structure. MCMC simulation techniques are required in order to approach the non-analytically tractable posterior distribution of the model parameters. The predictive distribution is then estimated using Monte Carlo integration. A Bayesian model selection crite…
Analysing the mediating role of a network: a Bayesian latent space approach
2020
The use of network analysis for the investigation of social structures has recently seen a rise, due both to the high availability of data and to the numerous insights it can provide into different fields. Most analyses focus on the topological characteristics of networks and the estimation of relationships between the nodes. We adopt a different point of view, by considering the whole network as a random variable conveying the effect of an exposure on a response. This point of view represents a classical mediation setting, where the interest lies in the estimation of the indirect effect, that is, the effect propagated through the mediating variable. We introduce a latent space model mappin…
A Physiological Approach for Minimizing Dead Reckoning Velocity Readings Drifts
2018
The evolution of the geo-positioning methods made Dead Reckoning (DR) one of the most important concern due to its performance in indoor pedestrian localization systems. This paper focuses on implementing an approach that relies on physiological parameters to minimize additive velocity error due to noise in pedestrian DR system.
Updated determination of the solar neutrino fluxes from solar neutrino data
2016
Journal of High Energy Physics 2016.3 (2016): 132 reproduced by permission of Scuola Internazionale Superiore di Studi Avanzati (SISSA)
Privacy preserving via tree augmented naïve Bayesian classifier in multimedia database
2011
International audience; In this paper, we propose a novel technique for privacy preserving in multimedia databases. Our technique is based on a multimedia co-occurrence matrix and a tree augmented naive Bayesian classifier (TAN) to detect possible data associations making confidential multimedia objects at risk.
Search for two-neutrino double electron capture of $^{124}$Xe with XENON100
2017
Two-neutrino double electron capture is a rare nuclear decay where two electrons are simultaneously captured from the atomic shell. For $^{124}$Xe this process has not yet been observed and its detection would provide a new reference for nuclear matrix element calculations. We have conducted a search for two-neutrino double electron capture from the K-shell of $^{124}$Xe using 7636 kg$\cdot$d of data from the XENON100 dark matter detector. Using a Bayesian analysis we observed no significant excess above background, leading to a lower 90 % credibility limit on the half-life $T_{1/2}>6.5\times10^{20}$ yr. We also evaluated the sensitivity of the XENON1T experiment, which is currently bein…
Multivariate exponential smoothing: A Bayesian forecast approach based on simulation
2009
This paper deals with the prediction of time series with correlated errors at each time point using a Bayesian forecast approach based on the multivariate Holt-Winters model. Assuming that each of the univariate time series comes from the univariate Holt-Winters model, all of them sharing a common structure, the multivariate Holt-Winters model can be formulated as a traditional multivariate regression model. This formulation facilitates obtaining the posterior distribution of the model parameters, which is not analytically tractable: simulation is needed. An acceptance sampling procedure is used in order to obtain a sample from this posterior distribution. Using Monte Carlo integration the …
BEM-Based Magnetic Field Reconstruction by Ensemble Kálmán Filtering
2022
Abstract Magnetic fields generated by normal or superconducting electromagnets are used to guide and focus particle beams in storage rings, synchrotron light sources, mass spectrometers, and beamlines for radiotherapy. The accurate determination of the magnetic field by measurement is critical for the prediction of the particle beam trajectory and hence the design of the accelerator complex. In this context, state-of-the-art numerical field computation makes use of boundary-element methods (BEM) to express the magnetic field. This enables the accurate computation of higher-order partial derivatives and local expansions of magnetic potentials used in efficient numerical codes for particle tr…
Classification and retrieval on macroinvertebrate image databases
2011
Aquatic ecosystems are continuously threatened by a growing number of human induced changes. Macroinvertebrate biomonitoring is particularly efficient in pinpointing the cause-effect structure between slow and subtle changes and their detrimental consequences in aquatic ecosystems. The greatest obstacle to implementing efficient biomonitoring is currently the cost-intensive human expert taxonomic identification of samples. While there is evidence that automated recognition techniques can match human taxa identification accuracy at greatly reduced costs, so far the development of automated identification techniques for aquatic organisms has been minimal. In this paper, we focus on advancing …
A Novel Bayesian Network Based Scheme for Finding the Optimal Solution to Stochastic Online Equi-partitioning Problems
2014
A number of intriguing decision scenarios, such as order picking, revolve around partitioning a collection of objects so as to optimize some application specific objective function. In its general form, this problem is referred to as the Object Partitioning Problem (OOP), known to be NP-hard. We here consider a variant of OPP, namely the Stochastic Online Equi-Partitioning Problem (SO-EPP). In SO-EPP, objects arrive sequentially, in pairs. The relationship between the arriving object pairs is stochastic: They belong to the same partition with probability p. From a history of object arrivals, the goal is to predict which objects will appear together in future arrivals. As an additional compl…