Search results for "Data type"

showing 10 items of 1183 documents

Analyzing Temperature Effects on Mortality Within theREnvironment: The Constrained Segmented Distributed Lag Parameterization

2010

Here we present and discuss the R package modTempEff including a set of functions aimed at modelling temperature effects on mortality with time series data. The functions fit a particular log linear model which allows to capture the two main features of mortality- temperature relationships: nonlinearity and distributed lag effect. Penalized splines and segmented regression constitute the core of the modelling framework. We briefly review the model and illustrate the functions throughout a simulated dataset.

Statistics and ProbabilityDistributed lagtemperature effects segmented relationship break point P-splines RMathematical optimizationComputer scienceP-splinesRsegmented relationshipSet (abstract data type)R packageNonlinear systemBreak pointApplied mathematicsLog-linear modelbreak pointStatistics Probability and UncertaintySegmented regressionTime seriesSettore SECS-S/01 - Statisticatemperature effectslcsh:Statisticslcsh:HA1-4737SoftwareJournal of Statistical Software
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Ranking Scientific Journals Via Latent Class Models for Polytomous Item Response Data

2015

Summary We propose a model-based strategy for ranking scientific journals starting from a set of observed bibliometric indicators that represent imperfect measures of the unobserved ‘value’ of a journal. After discretizing the available indicators, we estimate an extended latent class model for polytomous item response data and use the estimated model to cluster journals. We illustrate our approach by using the data from the Italian research evaluation exercise that was carried out for the period 2004–2010, focusing on the set of journals that are considered relevant for the subarea statistics and financial mathematics. Using four bibliometric indicators (IF, IF5, AIS and the h-index), some…

Statistics and ProbabilityEconomics and EconometricEconomics and EconometricsClass (set theory)Research evaluationClusteringSet (abstract data type)Valutazione della Qualità delle RicercaCovariateStatisticsEconometricsFinite mixture modelsCluster analysisFinite mixture modelMathematicsGraded response modelMathematical financeItem response theory modelsItem response theory modelProbability and statisticsLatent class modelRankingStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaValutazione della Qualità delle Ricerca; Clustering; Finite mixture models; Graded response model; Item response theory models; Research evaluation;Social Sciences (miscellaneous)Journal of the Royal Statistical Society Series A: Statistics in Society
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Study Design in Causal Models

2014

The causal assumptions, the study design and the data are the elements required for scientific inference in empirical research. The research is adequately communicated only if all of these elements and their relations are described precisely. Causal models with design describe the study design and the missing-data mechanism together with the causal structure and allow the direct application of causal calculus in the estimation of the causal effects. The flow of the study is visualized by ordering the nodes of the causal diagram in two dimensions by their causal order and the time of the observation. Conclusions on whether a causal or observational relationship can be estimated from the coll…

Statistics and ProbabilityEmpirical researchTheoretical computer scienceGraph (abstract data type)Graphical modelStatistics Probability and UncertaintyCausal structureMissing dataCausalityStructural equation modelingCausal modelMathematicsScandinavian Journal of Statistics
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The conditional censored graphical lasso estimator

2020

© 2020, Springer Science+Business Media, LLC, part of Springer Nature. In many applied fields, such as genomics, different types of data are collected on the same system, and it is not uncommon that some of these datasets are subject to censoring as a result of the measurement technologies used, such as data generated by polymerase chain reactions and flow cytometer. When the overall objective is that of network inference, at possibly different levels of a system, information coming from different sources and/or different steps of the analysis can be integrated into one model with the use of conditional graphical models. In this paper, we develop a doubly penalized inferential procedure for…

Statistics and ProbabilityFOS: Computer and information sciencesComputer scienceGaussianInferenceData typeTheoretical Computer Sciencehigh-dimensional settingDatabase normalizationMethodology (stat.ME)symbols.namesakeLasso (statistics)Graphical modelConditional Gaussian graphical modelcensored graphical lassoStatistics - MethodologyHigh-dimensional settingconditional Gaussian graphical modelssparsityEstimatorCensoring (statistics)Censored graphical lassoComputational Theory and MathematicssymbolsCensored dataStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaSparsityAlgorithm
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Adaptive reference-free compression of sequence quality scores

2014

Motivation: Rapid technological progress in DNA sequencing has stimulated interest in compressing the vast datasets that are now routinely produced. Relatively little attention has been paid to compressing the quality scores that are assigned to each sequence, even though these scores may be harder to compress than the sequences themselves. By aggregating a set of reads into a compressed index, we find that the majority of bases can be predicted from the sequence of bases that are adjacent to them and hence are likely to be less informative for variant calling or other applications. The quality scores for such bases are aggressively compressed, leaving a relatively small number at full reso…

Statistics and ProbabilityFOS: Computer and information sciencesComputer sciencemedia_common.quotation_subjectReference-freecomputer.software_genreBiochemistryDNA sequencingSet (abstract data type)Redundancy (information theory)BWTComputer Science - Data Structures and AlgorithmsCode (cryptography)AnimalsHumansQuality (business)Data Structures and Algorithms (cs.DS)Quantitative Biology - GenomicsCaenorhabditis elegansMolecular Biologymedia_commonGenomics (q-bio.GN)SequenceGenomeSettore INF/01 - Informaticareference-free compressionHigh-Throughput Nucleotide SequencingGenomicsSequence Analysis DNAData CompressioncompressionComputer Science ApplicationsComputational MathematicsComputational Theory and MathematicsFOS: Biological sciencesData miningquality scoreMetagenomicscomputerBWT; compression; quality score; reference-free compressionAlgorithmsReference genome
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Comparative Evaluation of Community Detection Algorithms: A Topological Approach

2012

International audience; Community detection is one of the most active fields in complex networks analysis, due to its potential value in practical applications. Many works inspired by different paradigms are devoted to the development of algorithmic solutions allowing to reveal the network structure in such cohesive subgroups. Comparative studies reported in the literature usually rely on a performance measure considering the community structure as a partition (Rand Index, Normalized Mutual information, etc.). However, this type of comparison neglects the topological properties of the communities. In this article, we present a comprehensive comparative study of a representative set of commu…

Statistics and ProbabilityFOS: Computer and information sciencesPhysics - Physics and SocietyComputer science[INFO.INFO-OH]Computer Science [cs]/Other [cs.OH]Rand indexFOS: Physical sciences02 engineering and technologyPhysics and Society (physics.soc-ph)Topology01 natural sciencesMeasure (mathematics)010305 fluids & plasmasSet (abstract data type)Development (topology)0103 physical sciences0202 electrical engineering electronic engineering information engineeringEquivalence (measure theory)Random graphSocial and Information Networks (cs.SI)Computer Science - Social and Information NetworksStatistical and Nonlinear PhysicsNetwork dynamicsPartition (database)[ INFO.INFO-OH ] Computer Science [cs]/Other [cs.OH]020201 artificial intelligence & image processingStatistics Probability and Uncertainty
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Sharp dimension free quantitative estimates for the Gaussian isoperimetric inequality

2017

We provide a full quantitative version of the Gaussian isoperimetric inequality: the difference between the Gaussian perimeter of a given set and a half-space with the same mass controls the gap between the norms of the corresponding barycenters. In particular, it controls the Gaussian measure of the symmetric difference between the set and the half-space oriented so to have the barycenter in the same direction of the set. Our estimate is independent of the dimension, sharp on the decay rate with respect to the gap and with optimal dependence on the mass.

Statistics and ProbabilityGaussianGaussian isoperimetric inequality01 natural sciencesPerimeterSet (abstract data type)symbols.namesakeMathematics - Analysis of PDEsDimension (vector space)quantitative isoperimetric inequalityFOS: MathematicsMathematics::Metric Geometry0101 mathematicsSymmetric differenceGaussian isoperimetric inequalityQuantitative estimatesMathematics010102 general mathematicsMathematical analysisProbability (math.PR)49Q20Gaussian measure010101 applied mathematicssymbolsHigh Energy Physics::Experiment60E15Statistics Probability and UncertaintyMathematics - ProbabilityAnalysis of PDEs (math.AP)
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A geostatistical approach for dynamic life tables: The effect of mortality on remaining lifetime and annuities

2010

Dynamic life tables arise as an alternative to the standard (static) life table, with the aim of incorporating the evolution of mortality over time. The parametric model introduced by Lee and Carter in 1992 for projected mortality rates in the US is one of the most outstanding and has been used a great deal since then. Different versions of the model have been developed but all of them, together with other parametric models, consider the observed mortality rates as independent observations. This is a difficult hypothesis to justify when looking at the graph of the residuals obtained with any of these methods. Methods of adjustment and prediction based on geostatistical techniques which expl…

Statistics and ProbabilityLife tableEconomics and EconometricsESTADISTICA E INVESTIGACION OPERATIVAStructure (category theory)Variation (game tree)GeostatisticsTable (information)GridParametric modelStatisticsEconometricsGraph (abstract data type)GeostatisticsStatistics Probability and UncertaintyBootstrap confidence intervalMathematicsBootstrap confidence intervals
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Noise-induced resistive switching in a memristor based on ZrO2(Y)/Ta2O5 stack

2019

Resistive switching (RS) is studied in a memristor based on a ZrO2(Y)/Ta2O5 stack under a white Gaussian noise voltage signal. We have found that the memristor switches between the low resistance state and the high resistance state in a random telegraphic signal (RTS) mode. The effective potential profile of the memristor shows from two to three local minima and depends on the input noise parameters and the memristor operation. These observations indicate the multiplicative character of the noise on the dynamical behavior of the memristor, that is the noise perceived by the memristor depends on the state of the system and its electrical properties are influenced by the noise signal. The det…

Statistics and ProbabilityMaterials sciencebusiness.industryNoise inducedStatistical and Nonlinear PhysicsMemristorStochastic particle dynamicslaw.inventionDiffusionStack (abstract data type)lawResistive switchingOptoelectronicsFluctuation phenomenaStatistics Probability and UncertaintyBrownian motionbusiness
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STATIS and DISTATIS: optimum multitable principal component analysis and three way metric multidimensional scaling

2012

STATIS is an extension of principal component analysis PCA tailored to handle multiple data tables that measure sets of variables collected on the same observations, or, alternatively, as in a variant called dual-STATIS, multiple data tables where the same variables are measured on different sets of observations. STATIS proceeds in two steps: First it analyzes the between data table similarity structure and derives from this analysis an optimal set of weights that are used to compute a linear combination of the data tables called the compromise that best represents the information common to the different data tables; Second, the PCA of this compromise gives an optimal map of the observation…

Statistics and ProbabilityMathematical optimizationSimilarity (geometry)[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH]Linear discriminant analysiscomputer.software_genre01 natural sciences[ STAT.TH ] Statistics [stat]/Statistics Theory [stat.TH]Correspondence analysisSet (abstract data type)010104 statistics & probability03 medical and health sciences0302 clinical medicine[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]Multiple factor analysisPrincipal component analysisMetric (mathematics)Data miningMultidimensional scaling[ MATH.MATH-ST ] Mathematics [math]/Statistics [math.ST]0101 mathematicscomputer030217 neurology & neurosurgeryComputingMilieux_MISCELLANEOUSMathematics
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