Search results for "Principal Component Analysis"

showing 10 items of 486 documents

STATISTICAL METHODS FOR THE DISCRIMINATION OF FOUR FORMS OF DIPLEGIA

FUNCTIONAL PRINCIPAL COMPONENT ANALYSISLINEAR DISCRIMINANT MODELDIPLEGIA
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Forecasting Financial Crises and Contagion in Asia Using Dynamic Factor Analysis

2009

In this paper we use principal components analysis to obtain vulnerability indicators able to predict financial turmoil. Probit modelling through principal components and also stochastic simulation of a Dynamic Factor model are used to produce the corresponding probability forecasts regarding the currency crisis events affecting a number of East Asian countries during the 1997-1998 period. The principal components model improves upon a number of competing models, in terms of out-of-sample forecasting performance.

FinanceFinancial contagionbusiness.industryDynamic factorStochastic simulationPrincipal component analysisEconomicsVulnerabilityProbitEast AsiabusinessCurrency crisisSSRN Electronic Journal
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The peach volatilome modularity is reflected at the genetic and environmental response levels in a QTL mapping population

2014

Background: The improvement of fruit aroma is currently one of the most sought-after objectives in peach breeding programs. To better characterize and assess the genetic potential for increasing aroma quality by breeding, a quantity trait locus (QTL) analysis approach was carried out in an F-1 population segregating largely for fruit traits. Results: Linkage maps were constructed using the IPSC peach 9 K Infinium (R) II array, rendering dense genetic maps, except in the case of certain chromosomes, probably due to identity-by-descent of those chromosomes in the parental genotypes. The variability in compounds associated with aroma was analyzed by a metabolomic approach based on GC-MS to pro…

FitomejoramientoVolatile CompoundsGenotyping TechniquesQuantitative Trait LociPopulationLocus (genetics)Plant ScienceBreedingEnvironmentQuantitative trait locusPolymorphism Single NucleotideCompuesto VolátilPrunusMetabolomicsQTL (Quantitative Trait Loci)Databases GeneticGenotypeCluster AnalysisPrunus PersicaGene Regulatory NetworkseducationAromaAromaLoci de Rasgos CuantitativosGeneticsPrincipal Component AnalysisVolatile Organic Compoundseducation.field_of_studybiologyDuraznoChromosome Mappingfood and beveragesbiology.organism_classificationPlant BreedingFruitPeachesMetabolomeTraitPrunusLod ScoreResearch ArticleBMC Plant Biology
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An innovative method to produce green table olives based on "pied de cuve" technology

2015

The technology of “pied de cuve” (PdC) is applied in food process only to produce wines with an enriched community of pro-technological yeasts. PdC promotes the growth of the desirable microbial strains in a small volume of grape must acting as a starter inoculums for higher volumes. The aim of the present work was to investigate the use of partially fermented brines, a technology known as PdC, developed with lactic acid bacteria (LAB) on the microbiological, chemical and sensory characteristics of green fermented table olives during two consecutive campaigns. The experimental plan included two trials based on different PdCs: trial A, PdC obtained with Lactobacillus pentosus OM13; trial B, …

Food HandlingLactic acid bacteria; Lactobacillus pentosus; Nocellara del Belice table olive; Pied de cuve; Volatile organic compounds; Yeasts; Food Science; MicrobiologyColony Count MicrobialLactobacillus pentosusSensory analysisMicrobiologychemistry.chemical_compoundStarterOleaYeastsLactic acid bacteriaCluster AnalysisFood scienceAromaPrincipal Component AnalysisVolatile Organic Compoundsbiologybusiness.industrySmall volumeLactobacillus pentosufood and beverageshemic and immune systemsBiodiversitySettore AGR/15 - Scienze E Tecnologie AlimentariHydrogen-Ion ConcentrationVolatile organic compoundbiology.organism_classificationNocellara del Belice table oliveYeastBiotechnologyLactic acidSettore AGR/03 - Arboricoltura Generale E Coltivazioni ArboreeLactobacillusPhenotypechemistryTasteFermentationFood MicrobiologyFood TechnologyFermentationSaltsPied de cuvebusinessBacteriaFood ScienceSettore AGR/16 - Microbiologia Agraria
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Chemical Element Levels as a Methodological Tool in Forensic Science

2014

The aim of the present study was to define a methodological strategy for understanding how post- mortem degradation in bones caused by the environment affects different skeletal parts and for selecting better preserved bone samples, employing rare earth elements (REEs) analysis and multivariate statistics. To test our methodological proposal the samples selected belong to adult and young individuals and were obtained from the Late Roman Necropolis of c/Virgen de la Misericordia located in Valencia city centre (Comunidad Valenciana, Spain). Therefore, a method for the determination of major elements, trace elements and REEs in bone remains has been developed employing Inductively-Coupled Pla…

Forensic scienceMultivariate statisticseducation.field_of_studyAnthropological science fictionStatisticsPartial least squares regressionPopulationPrincipal component analysisForensic chemistryBiologyeducationLinear discriminant analysisArchaeologyJournal of Forensic Research
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Capillary electrophoresis–inductively coupled plasma-mass spectrometry hyphenation for the determination at the nanogram scale of metal affinities an…

2012

Abstract A screening strategy based on hyphenated capillary electrophoresis and inductively coupled plasma mass spectrometry (CE–ICP-MS) was developed to classify phosphorylated ligands according to their europium(III) binding affinity in a hydro-organic medium (sodium formate, pH 3.7, H2O/MeOH 90:10, v/v). Taking advantage of the high sensibility of ICP-MS for detecting phosphorus, this method enabled to assess the affinity of a variety of phosphorylated compounds, including phosphine oxides, thiophosphines, phosphonates, and phosphinates, in less than 1 h and using less than 5 ng of substance. By varying the total europium concentration, complexation constants could be determined accordin…

Formateschemistry.chemical_elementLigandsLanthanoid Series ElementsBiochemistryMass SpectrometryAnalytical ChemistryMetalchemistry.chemical_compoundCapillary electrophoresisEuropiumLimit of DetectionInductively coupled plasma mass spectrometryPrincipal Component AnalysisChromatographySodium formateMethanolOrganic ChemistryElectrophoresis CapillaryReproducibility of ResultsGeneral MedicinePhosphorus Compoundschemistryvisual_artLinear Modelsvisual_art.visual_art_mediumThermodynamicsSpectrophotometry UltravioletTitrationAbsorption (chemistry)EuropiumPhosphineJournal of Chromatography A
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Table of Periodic Properties of Fullerenes Based on Structural Parameters.

2004

The periodic table (PT) of the elements suggests that hydrogen could be the origin of everything else. The construction principle is an evolutionary process that is formally similar to those of Darwin and Oparin. The Kekulé structure count and permanence of the adjacency matrix of fullerenes are related to structural parameters involving the presence of contiguous pentagons p, q and r. Let p be the number of edges common to two pentagons, q the number of vertices common to three pentagons, and r the number of pairs of nonadjacent pentagon edges shared between two other pentagons. Principal component analysis (PCA) of the structural parameters and cluster analysis (CA) of the fullerenes perm…

FullereneChemistryGeneral ChemistryGeneral MedicineComputer Science ApplicationsPentagonCombinatoricsAlgebraCharacter (mathematics)Computational Theory and MathematicsPrincipal component analysisCluster (physics)Order (group theory)Rank (graph theory)Table (database)Adjacency matrixInformation SystemsMathematicsChemInform
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Principal components for multivariate spatiotemporal functional data

2014

Multivariate spatio-temporal data consist of a three way array with two dimensions’ domains both structured, temporally and spatially; think for example to a set of different pollutant levels recorded for a month/year at different sites. In this kind of dataset we can recognize time series along one dimension, spatial series along another and multivariate data along the third dimension. Statistical techniques aiming at handling huge amounts of information are very important in this context and classical dimension reduction techniques, such as Principal Components, are relevant, allowing to compress the information without much loss. Although time series, as well as spatial series, are recor…

Functional Data Analysis Functional Principal Component Analysis Multivariate Multidimensional DataSettore SECS-S/01 - Statistica
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Functional Data Analysis in NTCP Modeling: A New Method to Explore the Radiation Dose-Volume Effects

2014

Purpose/Objective(s) To describe a novel method to explore radiation dose-volume effects. Functional data analysis is used to investigate the information contained in differential dose-volume histograms. The method is applied to the normal tissue complication probability modeling of rectal bleeding (RB) for patients irradiated in the prostatic bed by 3-dimensional conformal radiation therapy. Methods and Materials Kernel density estimation was used to estimate the individual probability density functions from each of the 141 rectum differential dose-volume histograms. Functional principal component analysis was performed on the estimated probability density functions to explore the variatio…

Functional principal component analysisCancer ResearchMultivariate statisticsRadiationbusiness.industryKernel density estimationFunctional data analysisRegression analysisLogistic regressionConfidence intervalOncologyStatisticsPrincipal component analysisMedicineRadiology Nuclear Medicine and imagingNuclear medicinebusinessInternational Journal of Radiation Oncology*Biology*Physics
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Comparing Spatial and Spatio-temporal FPCA to Impute Large Continuous Gaps in Space

2018

Multivariate spatio-temporal data analysis methods usually assume fairly complete data, while a number of gaps often occur along time or in space. In air quality data long gaps may be due to instrument malfunctions; moreover, not all the pollutants of interest are measured in all the monitoring stations of a network. In literature, many statistical methods have been proposed for imputing short sequences of missing values, but most of them are not valid when the fraction of missing values is high. Furthermore, the limitation of the methods commonly used consists in exploiting temporal only, or spatial only, correlation of the data. The objective of this paper is to provide an approach based …

Functional principal component analysisComplete dataMultivariate statisticsLong gapComputer sciencecomputer.software_genreMissing dataCorrelationFDA FPCA GAM P-splinesData analysisData miningImputation (statistics)Settore SECS-S/01 - Statisticacomputer
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