Search results for "ESTIMATOR"

showing 10 items of 313 documents

Stochastic discretized learning-based weak estimation: a novel estimation method for non-stationary environments

2016

The task of designing estimators that are able to track time-varying distributions has found promising applications in many real-life problems.Existing approaches resort to sliding windows that track changes by discarding old observations. In this paper, we report a novel estimator referred to as the Stochastic Discretized Weak Estimator (SDWE), that is based on the principles of discretized Learning Automata (LA). In brief, the estimator is able to estimate the parameters of a time varying binomial distribution using finite memory. The estimator tracks changes in the distribution by operating a controlled random walk in a discretized probability space. The steps of the estimator are discre…

Learning automataEstimator020206 networking & telecommunications02 engineering and technologyBinomial distributionUnivariate distributionEfficient estimatorArtificial IntelligenceSignal Processing0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingMultinomial distributionComputer Vision and Pattern RecognitionMinimax estimatorAlgorithmSoftwareInvariant estimatorMathematicsPattern Recognition
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Robust estimation of mean electricity consumption curves by sampling for small areas in presence of missing values

2017

In this thesis, we address the problem of robust estimation of mean or total electricity consumption curves by sampling in a finite population for the entire population and for small areas. We are also interested in estimating mean curves by sampling in presence of partially missing trajectories.Indeed, many studies carried out in the French electricity company EDF, for marketing or power grid management purposes, are based on the analysis of mean or total electricity consumption curves at a fine time scale, for different groups of clients sharing some common characteristics.Because of privacy issues and financial costs, it is not possible to measure the electricity consumption curve of eac…

Linear mixed modelsSmall area estimationMissing dataRegression treesEstimation sur petits domaines[MATH.MATH-GM] Mathematics [math]/General Mathematics [math.GM]Estimateurs à noyauModèles linéaires mixtesRandom forestsBiais conditionnelsFunctional dataSurvey sampling[MATH.MATH-GM]Mathematics [math]/General Mathematics [math.GM]RobustesseDonnées fonctionnellesPlus proches voisinsForêts aléatoiresConditional biasKernel estimatorsNearest neighboursSondageDonnées manquantesRobustnessArbres de régression
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Is the ‘euro effect’ on trade so small after all? New evidence using gravity equations with panel cointegration techniques

2014

In this paper we present new evidence on the aggregate effect of the euro on trade using data for 26 OECD countries for the period 1967–2008. We strive to fill the gaps present in the previous literature through a second-generation panel cointegration tests and estimators that account for both cross-section dependence in the data and discontinuities in the deterministic and the cointegrating vector in the time dimension. This approach allows us to put the adoption of the euro by EMU members in historical perspective. We argue that the creation of the EMU is best interpreted as a progression of policy changes. Once we control for all of them the euro effect decreases considerably but is stil…

MacroeconomicsEconomics and EconometricsCointegrationAggregate (data warehouse)EstimatorOecd countriesGravity modelsPanel cointegrationMultiple time dimensionsEconomicsEconometricsCross-section dependenceTradeStructural breaksCommon factorsFinance
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Accelerated Proximal Gradient Descent in Metric Learning for Kernel Regression

2018

The purpose of this paper is to learn a specific distance function for the Nadayara Watson estimator to be applied as a non-linear classifier. The idea of transforming the predictor variables and learning a kernel function based on Mahalanobis pseudo distance througth an low rank structure in the distance function will help us to lead the development of this problem. In context of metric learning for kernel regression, we introduce an Accelerated Proximal Gradient to solve the non-convex optimization problem with better convergence rate than gradient descent. An extensive experiment and the corresponding discussion tries to show that our strategie its a competitive solution in relation to p…

Mahalanobis distanceOptimization problembusiness.industryComputer scienceEstimator02 engineering and technology010501 environmental sciences01 natural sciencesRate of convergenceMetric (mathematics)0202 electrical engineering electronic engineering information engineeringKernel regression020201 artificial intelligence & image processingArtificial intelligencebusinessGradient descentAlgorithmClassifier (UML)0105 earth and related environmental sciences
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Overrating Classifier Performance in ROC Analysis in the Absence of a Test Set: Evidence from Simulation and Italian CARATkids Validation

2019

Background The use of receiver operating characteristic curves, or “ROC analysis,” has become quite common in biomedical research to support decisions. However, sensitivity, specificity, and misclassification rates are still often estimated using the training sample, overlooking the risk of overrating the test performance. Methods A simulation study was performed to highlight the inferential implications of splitting (or not) the dataset into training and test set. The normality assumption was made for the classifier given the disease status, and the Youden's criterion considered for the detection of the optimal cutoff. Then, an ROC analysis with sample split was applied to assess the disc…

Male020205 medical informaticsperformance estimatorsmedia_common.quotation_subjectHealth Informatics02 engineering and technology03 medical and health sciences0302 clinical medicineHealth Information ManagementSurveys and QuestionnairesStatisticstrue predictive performanceRinite Alérgica0202 electrical engineering electronic engineering information engineeringmedicineHumanssample splitComputer Simulation030212 general & internal medicineChildAsmaNormalityAsthmaMathematicsmedia_commonAdvanced and Specialized NursingReceiver operating characteristicasthma control testasthma control test sample split performance estimators optimal cutoff simulation study true predictive performanceDiscriminant validityReproducibility of ResultsEstimatormedicine.diseasesimulation studyRhinitis AllergicAsthmaConfidence intervalROC CurveTest setoptimal cutoffFemaleClassifier (UML)
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Sample size planning of two-arm superiority and noninferiority survival studies with discrete follow-up

2016

In clinical trials using lifetime as primary outcome variable, it is more the rule than the exception that even for patients who are failing in the course of the study, survival time does not become known exactly since follow-up takes place according to a restricted schedule with fixed, possibly long intervals between successive visits. In practice, the discreteness of the data obtained under such circumstances is plainly ignored both in data analysis and in sample size planning of survival time studies. As a framework for analyzing the impact of making no difference between continuous and discrete recording of failure times, we use a scenario in which the partially observed times are assig…

Male0301 basic medicineStatistics and ProbabilityScheduleTime FactorsEpidemiologyBiostatistics01 natural sciences010104 statistics & probability03 medical and health sciencesStatisticsEconometricsHumans0101 mathematicsRepresentation (mathematics)Proportional Hazards ModelsMathematicsClinical Trials as TopicLikelihood FunctionsModels StatisticalProstatic NeoplasmsEstimatorGridSurvival AnalysisConfidence intervalAlcoholismVariable (computer science)030104 developmental biologySample size determinationSample SizeParametric modelFollow-Up StudiesStatistics in Medicine
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Sensitivity of Estimators for Measuring Information Amount in Web-Based Medical Documents

2018

Nowadays, communication between patient and doctor during an appointment has changed significantly owning to the opportunity that medical portals provide. Whether or not necessarily appreciated by the doctors, the patients became more aware of the first symptoms’ suggesting a particular disease and the medical procedures that apply as a standard. Estimating amount of reliable factual medical information in a document is carried out by parametrizing space of digital documents and dividing it into subsequent layers that represent distribution of the system responses computed as random variables to a query about medical information. Analyzed are the following attributes: dynamism of decrease o…

Matching (statistics)021103 operations researchInformation retrievalMedical terminology020205 medical informaticsComputer sciencebusiness.industry0211 other engineering and technologiesEstimator02 engineering and technologySpace (commercial competition)Identification (information)Metric space0202 electrical engineering electronic engineering information engineeringWeb applicationbusinessRandom variable2018 Thirteenth International Conference on Digital Information Management (ICDIM)
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Piezoelectric coefficients by molecular dynamics simulations in the constant stress ensemble: A case study of quartz

2006

Piezoelectric (strain) coefficients dij of quartz are calculated in terms of molecular dynamics as a function of pressure and temperature. We review the necessary formulas for the computation of electromechanical materials coefficients obtained at constant stress and temperature, and discuss how to overcome complications of the definition of polarization variations due to fluctuating box geometries. A method is employed suppressing significantly stochastic fluctuations of the estimators for piezoelectric coefficients. A recently suggested force field for the simulation of SiO2 reproduces available experimental data quite accurately. Predictions are made for the pressure dependence of dij of…

Materials scienceComputationGeneral Physics and AstronomyEstimatorMechanicsPolarization (waves)PiezoelectricityForce field (chemistry)Condensed Matter::Materials ScienceMolecular dynamicsHardware and ArchitectureConstant stressStatistical physicsQuartzComputer Physics Communications
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Bayesian estimation of edge orientations in junctions

1999

Abstract Junctions, defined as those points of an image where two or more edges meet, play a significant role in many computer vision applications. Junction detection is a widely treated problem, and some detectors can provide even the directions of the edges that meet in a junction. The main objective of this paper is the precise estimation of such directions. It is supposed that the junction point has been previously found by some detector. Also, it is assumed that samples, possibly noisy, of orientations of the edges found in a circular window surrounding the point are available. A mixture of von Mises distributions is assumed for these data, and then a Bayesian methodology is applied to…

Mathematical optimizationBayes estimatorBayesian probabilityDetectorPosterior probabilityMarkov chain Monte CarloExpected valueReal imagesymbols.namesakeArtificial IntelligenceSignal ProcessingsymbolsPoint (geometry)Computer Vision and Pattern RecognitionAlgorithmSoftwareMathematicsPattern Recognition Letters
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A novel Stochastic Discretized Weak Estimator operating in non-stationary environments

2012

The task of designing estimators that are able to track time-varying distributions has found promising applications in many real-life problems. A particularly interesting family of distributions are the binomial/multiomial distributions. Existing approaches resort to sliding windows that track changes by discarding old observations. In this paper, we report a novel estimator referred to as the Stochastic Discretized Weak Estimator (SDWE), that is based on the principles of Learning Automata (LA). In brief, the estimator is able to estimate the parameters of a time varying binomial distribution using finite memory. The estimator tracks changes in the distribution by operating on a controlled…

Mathematical optimizationDelta methodMinimum-variance unbiased estimatorEfficient estimatorConsistent estimatorStein's unbiased risk estimateApplied mathematicsEstimatorTrimmed estimatorInvariant estimatorMathematics2012 International Conference on Computing, Networking and Communications (ICNC)
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