Search results for " regression [Classificació AMS]"

showing 10 items of 162 documents

Clusters of effects curves in quantile regression models

2018

In this paper, we propose a new method for finding similarity of effects based on quantile regression models. Clustering of effects curves (CEC) techniques are applied to quantile regression coefficients, which are one-to-one functions of the order of the quantile. We adopt the quantile regression coefficients modeling (QRCM) framework to describe the functional form of the coefficient functions by means of parametric models. The proposed method can be utilized to cluster the effect of covariates with a univariate response variable, or to cluster a multivariate outcome. We report simulation results, comparing our approach with the existing techniques. The idea of combining CEC with QRCM per…

Statistics and ProbabilityStatistics::TheoryMultivariate statistics05 social sciencesUnivariateFunctional data analysis01 natural sciencesQuantile regressionQuantile regression coefficients modeling Multivariate analysis Functional data analysis Curves clustering Variable selection010104 statistics & probabilityComputational Mathematics0502 economics and businessParametric modelCovariateStatistics::MethodologyApplied mathematics0101 mathematicsStatistics Probability and UncertaintyCluster analysisSettore SECS-S/01 - Statistica050205 econometrics MathematicsQuantile
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Nonlinear parametric quantile models

2020

Quantile regression is widely used to estimate conditional quantiles of an outcome variable of interest given covariates. This method can estimate one quantile at a time without imposing any constraints on the quantile process other than the linear combination of covariates and parameters specified by the regression model. While this is a flexible modeling tool, it generally yields erratic estimates of conditional quantiles and regression coefficients. Recently, parametric models for the regression coefficients have been proposed that can help balance bias and sampling variability. So far, however, only models that are linear in the parameters and covariates have been explored. This paper …

Statistics and ProbabilityStatistics::Theoryquantile regressionEpidemiologyparametric010501 environmental sciences01 natural sciencesquantile regression coefficients models010104 statistics & probabilityOutcome variableHealth Information ManagementCovariateEconometricsHumansStatistics::MethodologyComputer Simulation0101 mathematicsChild0105 earth and related environmental sciencesParametric statisticsMathematicsModels StatisticalForced oscillation technique integrated loss function parametric quantile regression quantile regression coefficients models Child Computer Simulation Humans Regression Analysis Models Statistical Nonlinear DynamicsStatistics::ComputationQuantile regressionNonlinear systemNonlinear Dynamicsintegrated loss functionRegression AnalysisQuantileStatistical Methods in Medical Research
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Substituent effects on13C NMR parameters of chlorinated diphenyl ethers. A multiple linear regression analysis

1995

13C NMR chemical shifts and nJ(C,H) coupling constants of polychlorinated diphenyl ethers (PCDEs) were measured and analysed. The chlorine substituent effects on the chemical shifts and the coupling constants were determined by a multiple linear regression analysis. The 13C NMR chemical shifts depend on the conformational preferences in PCDEs. In addition to single substituent effects, corrective terms reflecting the conformational state of the molecule and the mutual steric interactions of two chlorine atoms had to be taken into account for the reliable prediction of the 13C chemical shifts. In contrast to chemical shifts, conformational effects play a minor role in the substituent effects…

Steric effectsCoupling constantChemistryStereochemistryChemical shiftSubstituentGeneral ChemistryCarbon-13 NMRPolychlorinated diphenyl etherschemistry.chemical_compoundComputational chemistryMoleculeGeneral Materials ScienceMultiple linear regression analysisMagnetic Resonance in Chemistry
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Disentangling cardiovascular control mechanisms during head-down tilt via joint transfer entropy and self-entropy decompositions

2015

A full decomposition of the predictive entropy (PE) of the spontaneous variations of the heart period (HP) given systolic arterial pressure (SAP) and respiration (R) is proposed. The PE of HP is decomposed into the joint transfer entropy (JTE) from SAP and R to HP and self-entropy (SE) of HP. The SE is the sum of three terms quantifying the synergistic/redundant contributions of HP and SAP, when taken individually and jointly, to SE and one term conditioned on HP and SAP denoted as the conditional SE (CSE) of HP given SAP and R. The JTE from SAP and R to HP is the sum of two terms attributable to SAP or R plus an extra term describing the redundant/synergistic contribution to the JTE. All q…

Supine positionInformation storageComputer sciencePhysiologyAutonomic nervous system; Baroreflex; Blood pressure variability; Cardiopulmonary coupling; Heart rate variability; Information dynamics; Multivariate linear regression analysis; Physiology; Physiology (medical)Cardiovascular controlAutonomic Nervous Systemlcsh:PhysiologyNuclear magnetic resonanceCardiopulmonary couplingPhysiology (medical)Cardiac controlHeart rate variabilityOriginal Researchlcsh:QP1-981redundancymultivariate linear regression analysiscardiopulmonary couplingBaroreflexHead-Down TiltInformation dynamicSynergySettore ING-INF/06 - Bioingegneria Elettronica E InformaticaSystolic arterial pressureTransfer entropyblood pressure variabilityMultivariate linear regression analysiinformation dynamicsAlgorithmFrontiers in Physiology
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Relationship Between Extreme Rainfall and Surface Temperature in Sicily (Italy)

2018

The study of the relationship between extreme rainfall events and surface temperature represents an important issue in hydrology and meteorology and it could be of capital importance for evaluating the effect of global warming on future precipitation. Various approaches have been tested across different parts of the world, and, in many cases, it has been observed an intensification of precipitation with increasing temperature consistently with the thermodynamic Clausius-Clapeyron relation (CC-rate of 6-7% °C-1), according to which a warmer atmosphere is capable of holding more moisture. Nevertheless, in different locations, the scaling rate between temperature and extreme precipitation has …

Surface (mathematics)Clausius-Clapeyron Extreme rainfall TemperatureSettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaTemperatureEnvironmental scienceExtreme rainfallAtmospheric sciencesClausius-ClapeyronCC rate Sicily temperatureextreme rainfall regression model broken regression LOESS
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Predicting gully occurrence at watershed scale: Comparing topographic indices and multivariate statistical models

2020

In this study, the ability of five topographic indices to predict the gully trajectories observed in two adjacent watersheds located in Sicily (Italy) was evaluated. Two of these indices, named MSPI and MTWI, as far as we know, have never been employed to this aim. They were obtained by multiplying the stream power index (SPI) and the topographic wetness index (TWI), respectively, by the convergence index (CI). The predictive ability of the topographic indices was measured by using both cut-off independent (AUC: area under the receiver operating characteristic curve) and dependent statistics (Cohen's kappa index κ, sensitivity, specificity). These statistics were calculated also for 100 MAR…

Topographic Wetness IndexMultivariate Adaptive Regression Splines (MARS)Multivariate adaptive regression splinesIndex (economics)Watershed010504 meteorology & atmospheric sciencesReceiver operating characteristicStatistical modelMars Exploration Program010502 geochemistry & geophysicsLogistic regression01 natural sciencesTopographic indicesStatisticsGeographic Information System (GIS)Gully erosion susceptibilityGeologyLogistic Regression (LR)0105 earth and related environmental sciencesEarth-Surface Processes
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Ranking world tourist destinations with a composite indicator of competitiveness: To weigh or not to weigh?

2019

Abstract This paper contributes a weighted composite indicator of competitiveness for 136 world tourist destinations. To that end, Data Envelopment Analysis and Multi-Criteria-Decision-Making techniques are used with raw indicators from the 2017 edition of the Travel & Tourism Competitiveness Report of the World Economic Forum (WEF). An outstanding feature of our approach is that weights are endogenously generated. Furthermore, the role played by several variables in tourism competitiveness is assessed using truncated regression and bootstrapping. The ranking of world tourist destinations produced by our weighted composite indicator of competitiveness is, however, fairly similar to that der…

Truncated regression modelBootstrappingStrategy and Management05 social sciencesTransportationDevelopmentDestinationsComposite indicatorRankingTourism Leisure and Hospitality Management0502 economics and businessData envelopment analysisRegional scienceTourist destinations050211 marketingBusiness050212 sport leisure & tourismTourismTourism Management
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Gully Erosion Susceptibility Mapping Using Multivariate Adaptive Regression Splines—Replications and Sample Size Scenarios

2019

Soil erosion is a serious problem affecting numerous countries, especially, gully erosion. In the current research, GIS techniques and MARS (Multivariate Adaptive Regression Splines) algorithm were considered to evaluate gully erosion susceptibility mapping among others. The study was conducted in a specific section of the Gorganroud Watershed in Golestan Province (Northern Iran), covering 2142.64 km2 which is intensely influenced by gully erosion. First, Google Earth images, field surveys, and national reports were used to provide a gully-hedcut evaluation map consisting of 307 gully-hedcut points. Eighteen gully erosion conditioning factors including significant geoenvironmental and morph…

Watershedlcsh:Hydraulic engineering010504 meteorology & atmospheric sciencesCalibration (statistics)Settore GEO/04 - Geografia Fisica E GeomorfologiaGeography Planning and Development0207 environmental engineering02 engineering and technologyGully erosionrobustnessAquatic Science01 natural sciencesBiochemistrygislcsh:Water supply for domestic and industrial purposeslcsh:TC1-978Statisticsgully erosion susceptibility020701 environmental engineering0105 earth and related environmental sciencesWater Science and TechnologyMathematicslcsh:TD201-500Multivariate adaptive regression splinesReceiver operating characteristicMars Exploration Programmars algorithmSample size determinationSettore GEO/05 - Geologia ApplicataKappaWater
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Application of Molecular Topology to the Prediction of the Reaction Yield and Anticancer Activity of Imidazole and Guanidine Derivatives

2013

In this study molecular topology based QSAR has been applied to predict the reaction yield and anticancer activity of 18 imidazole and guanidine derivatives. Four properties were evaluated, namely reaction yield, anti prostatic-cancer activity, anti breast-cancer activity and anti lung-cancer activity. The four models have been validated by both internal and cross validation, and also by randomness tests. The results obtained are in full agreement with the experimental results and confirm the precision, accuracy and robustness of the method followed. After carrying out a virtual screening upon such models, new imidazole and guanidine derivatives with potential anticancer activity are propos…

chemistry.chemical_compoundVirtual screeningQuantitative structure–activity relationshipchemistryStereochemistryImidazoleMultiple linear regression analysisMolecular topologyCombinatorial chemistryGuanidine derivativesInternational Journal of Chemoinformatics and Chemical Engineering
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Evaluation of Hybrid Models to Estimate Chlorophyll and Nitrogen Content of Maize Crops in the Framework of the Future CHIME Mission

2022

In the next few years, the new Copernicus Hyperspectral Imaging Mission (CHIME) is foreseen to be launched by the European Space Agency (ESA). This mission will provide an unprecedented amount of hyperspectral data, enabling new research possibilities within several fields of natural resources, including the “agriculture and food security” domain. In order to efficiently exploit this upcoming hyperspectral data stream, new processing methods and techniques need to be studied and implemented. In this work, the hybrid approach (HYB) and its variant, featuring sampling dimensionality reduction through active learning heuristics (HAL), were applied to CHIME-like data to evaluate the…

chlorophyll contentmachine learning regression algorithmactive learningGeneral Earth and Planetary Sciencesspaceborne imaging spectroscopyradiative transfer modelingGaussian process regressionnitrogen contentRemote Sensing
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