Search results for "STATISTICS"

showing 10 items of 7671 documents

Dades massives i estadística: La perspectiva d'un estadístic

2014

Les dades massives (big data) representen un recurs sense precedents per a afrontar reptes científics, econòmics i socials, però també incrementen la possibilitat de traure conclusions enganyoses. Per exemple, l’ús d’enfocaments basats exclusivament en dades i que es despreocupen de comprendre el fenomen en estudi, que s’orienten a un objectiu esmunyedís i canviant, que no tenen en compte problemes determinants en la recopilació de dades, que resumeixen o «cuinen» inadequadament les dades i que confonen el soroll amb el senyal. Repassarem alguns casos reeixits i il·lustrarem com poden ajudar els principis de l’estadística a obtenir una informació més fiable de les dades. També abordarem els…

Computer scienceBig datadades massivespitfallsestudios de casocomputer sciencechallengesSocial issuescase studiesestadísticaHistory and Philosophy of Sciencebig dataPhenomenonPreprocessormacrodatosinformáticaMultidisciplinaryData collectionbusiness.industryPerspective (graphical)SIGNAL (programming language)estudis de casData sciencestatisticsbusinessStatistician
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Influence Diagnostics for Meta-Analysis of Individual Patient Data Using Generalized Linear Mixed Models

2014

In meta-analysis, generalized linear mixed models (GLMMs) are usually used when heterogeneity is present and individual patient data (IPD) are available, while accepting binary, discrete as well as continuous response variables. In the present paper some measures of influence diagnostics based on log-likelihood are suggested and discussed. A known measure is approximated to get a simpler form, for which the information matrix is no more necessary. The performance of the proposed measure is assessed through a diagnostic analysis on simulated data reproducing a possible meta-analytical context of IPD with influential outliers. The proposed measure is showed to work well and to have a form sim…

Computer scienceBinary numberContext (language use)Diagnostics Individual Patient Data Meta-Analysis OutliersMeasure (mathematics)Generalized linear mixed modelsymbols.namesakeMeta-analysisOutlierStatisticssymbolsSettore SECS-S/01 - StatisticaFisher informationAlgorithmStatistic
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Applicability of the Poisson distribution to model the data of the German Children's Cancer Registry.

1995

Since 1980 the German Children's Cancer Registry has documented all childhood malignancies in the Federal Republic of Germany. Various statistical procedures have been proposed to identify municipalities or other geographic units with increased numbers of malignancies. Usually the Poisson distribution, which requires the malignancies to be distributed homogeneously and uncorrelated, is applied. Other discrete statistical distributions (so-called cluster distributions) like the generalized or compound Poisson distributions are applicable more generally. In this paper we present a first explorative approach to the question of whether it is necessary to use one of these cluster distributions t…

Computer scienceBiophysicsPoisson distributionDisease clusterGermansymbols.namesakeGermanyNeoplasmsStatisticsEconometricsHumansPoisson DistributionRegistriesChildGeneral Environmental ScienceProbabilityRadiationModels StatisticalGermany WestFederal republic of germanylanguage.human_languageUncorrelatedCancer registrysymbolslanguageProbability distributionRadiation and environmental biophysics
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Vibrational spectroscopy provides a green tool for multi-component analysis

2010

Abstract Based on the literature published in the past decade, we focus on the possibilities offered by vibrational-spectroscopy-based techniques to make multi-component analysis of samples independently of their physical state. We discuss the main chemometric tools proposed for developing calibration models and solving problems derived from spectroscopic non-idealities (e.g., highly overlapped spectral bands or the presence of spectral non-linearity), and the benefits provided by vibrational-spectroscopy-based multi-component analysis in industry. Our main objective is to show that vibrational spectroscopy provides fast analytical methods that enable non-destructive analysis and permits, i…

Computer scienceCalibration (statistics)Infrared spectroscopyMineralogySample (statistics)Spectral bandscomputer.software_genreAnalytical ChemistryChemometricsNonlinear systemComponent analysisData miningFocus (optics)computerSpectroscopyTrAC Trends in Analytical Chemistry
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Power estimation for non-standardized multisite studies

2016

A concern for researchers planning multisite studies is that scanner and T1-weighted sequence-related biases on regional volumes could overshadow true effects, especially for studies with a heterogeneous set of scanners and sequences. Current approaches attempt to harmonize data by standardizing hardware, pulse sequences, and protocols, or by calibrating across sites using phantom-based corrections to ensure the same raw image intensities. We propose to avoid harmonization and phantom-based correction entirely. We hypothesized that the bias of estimated regional volumes is scaled between sites due to the contrast and gradient distortion differences between scanners and sequences. Given this…

Computer scienceCognitive Neurosciencecomputer.software_genreSensitivity and Specificity050105 experimental psychologyImaging phantomArticleSet (abstract data type)03 medical and health sciences0302 clinical medicineDistortionImage Interpretation Computer-AssistedCalibrationmedicine[INFO.INFO-IM]Computer Science [cs]/Medical ImagingHumans0501 psychology and cognitive sciencesSegmentationComputer Simulation10. No inequalityScalingModels Statisticalmedicine.diagnostic_test05 social sciencesContrast (statistics)BrainReproducibility of ResultsMagnetic resonance imagingEquipment DesignScale factorImage EnhancementMagnetic Resonance ImagingUnited StatesEquipment Failure AnalysisEuropeNeurologyOrdinary least squaresData miningFunction and Dysfunction of the Nervous SystemArtifactscomputer030217 neurology & neurosurgeryAlgorithms
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Colorimetric Characterization of Mobile Devices for Vision Applications

2015

Purpose: Available applications for vision testing in mobile devices usually do not include detailed setup instructions, sacrificing rigor to obtain portability and ease of use. In particular, colorimetric characterization processes are generally obviated. We show that different mobile devices differ also in colorimetric profile and that those differences limit the range of applications for which they are most adequate. Methods: The color reproduction characteristics of four mobile devices, two smartphones (Samsung Galaxy S4, iPhone 4s) and two tablets (Samsung Galaxy Tab 3, iPad 4), have been evaluated using two procedures: 3D LUT (Look Up Table) and a linear model assuming primary constan…

Computer scienceColor reproductionColorSoftware portabilityRange (statistics)HumansComputer visionIndependence (probability theory)ÓpticaColor differencebusiness.industryVision TestsUsabilityColorimetric characterizationOphthalmologyScreenComputers HandheldLookup tableLinear Models3D lookup tableColorimetryArtificial intelligenceSmartphonebusinessTabletMobile deviceOptometry
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On the Computation of Symmetrized M-Estimators of Scatter

2016

This paper focuses on the computational aspects of symmetrized Mestimators of scatter, i.e. the multivariate M-estimators of scatter computed on the pairwise differences of the data. Such estimators do not require a location estimate, and more importantly, they possess the important block and joint independence properties. These properties are needed, for example, when solving the independent component analysis problem. Classical and recently developed algorithms for computing the M-estimators and the symmetrized M-estimators are discussed. The effect of parallelization is considered as well as new computational approach based on using only a subset of pairwise differences. Efficiencies and…

Computer scienceComputation05 social sciencesEstimatorMultivariate normal distributionM-estimators01 natural sciencesIndependent component analysisscatter010104 statistics & probabilityScatter matrix0502 economics and businessPairwise comparison0101 mathematicsAlgorithmIndependence (probability theory)050205 econometrics Block (data storage)
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Correction to: a predictive model for women's assisted fecundity before starting the first IVF/ICSI treatment cycle.

2019

PURPOSE: To introduce a prognostic model for women’s assisted fecundity before starting the first IVF/ICSI treatment cycle. METHODS: In contrast to previous predictive models, we analyze two groups of women at the extremes of prognosis. Specifically, 708 infertile women that had either a live birth (LB) event in the first autologous IVF/ICSI cycle (“high-assisted-fecundity women”, n = 458) or did not succeed in having a LB event after completing three autologous IVF/ICSI cycles (“low-assisted-fecundity women”, n = 250). The initial sample of 708 women was split into two sets in order to develop (n = 531) and internally validate (n = 177) a predictive logistic regression model using a forwar…

Computer scienceComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKSObstetrics and GynecologyMistakeGeneral MedicineIvf icsiFecunditySet (abstract data type)Reproductive MedicineStatisticsGeneticsTable (database)Assisted Reproduction TechnologiesGenetics (clinical)Developmental BiologyJournal of assisted reproduction and genetics
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The impact of sample reduction on PCA-based feature extraction for supervised learning

2006

"The curse of dimensionality" is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimensions. In this paper, different feature extraction (FE) techniques are analyzed as means of dimensionality reduction, and constructive induction with respect to the performance of Naive Bayes classifier. When a data set contains a large number of instances, some sampling approach is applied to address the computational complexity of FE and classification processes. The main goal of this paper is to show the impact of sample reduction on the process of FE for supervised learning. In our study we analyzed the conventional PC…

Computer scienceCovariance matrixbusiness.industryDimensionality reductionFeature extractionSupervised learningNonparametric statisticsSampling (statistics)Pattern recognitionStratified samplingNaive Bayes classifierSample size determinationArtificial intelligencebusinessEigenvalues and eigenvectorsParametric statisticsCurse of dimensionalityProceedings of the 2006 ACM symposium on Applied computing
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The predictive power of game-related statistics for the final result under the rule changes introduced in the men’s world water polo championship: a …

2019

The objectives of this study were (i) to compare water polo game-related statistics by match outcome (winning and losing teams) after the application of the new rules, and (ii) to develop a classif...

Computer scienceDecision tree learningsports05 social sciencesPhysical Therapy Sports Therapy and Rehabilitation030229 sport sciencesWater poloOutcome (game theory)050105 experimental psychology03 medical and health sciences0302 clinical medicineStatisticsPredictive power0501 psychology and cognitive sciencesOrthopedics and Sports MedicineChampionshipsports.sports_positionInternational Journal of Performance Analysis in Sport
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