Search results for "Models"

showing 10 items of 8211 documents

Basic networks: Definition and applications

2009

7 pages, 4 figures, 1 table.-- PMID: 19490867 [PubMed]

Statistics and ProbabilityTheoretical computer scienceInteractomeGeodesicinteractomeSteiner tree problemModels BiologicalGeneral Biochemistry Genetics and Molecular BiologyGraph03 medical and health sciencessymbols.namesakeModuleProtein Interaction MappingmoduleAnimalsSteiner tree030304 developmental biologyMathematicsDiscrete mathematics0303 health sciencesModels StatisticalGeneral Immunology and MicrobiologyApplied Mathematics030302 biochemistry & molecular biologyGeneral MedicinegraphGraphModeling and SimulationsymbolsNeural Networks ComputerGeneral Agricultural and Biological SciencesAlgorithms
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Comment on "Ecological importance of the thermal emissivity of avian eggshells".

2012

Eggshell emissivity must be known to determine accurately the cooling rate of avian eggs when the parent, after heating by conduction during the incubation, is temporarily absent. We estimate possible values of eggshell emissivities from in-situ measurements and spectral libraries. Emissivity is near to 1 (probably higher than 0.95) and therefore its effect on cooling rate may be negligible, with differences between the temperature of the egg assuming a value of e=0.95 and that of a blackbody (e=1) below 0.2 °C.

Statistics and ProbabilityThermal infraredMaterials scienceGeneral Immunology and MicrobiologyEcologyApplied MathematicsGeneral MedicineThermal conductionModels BiologicalGeneral Biochemistry Genetics and Molecular BiologyBirdsEgg ShellCooling rateThermal radiationModeling and SimulationEmissivityAnimalsBlack-body radiationEggshellGeneral Agricultural and Biological SciencesBody Temperature RegulationJournal of theoretical biology
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Sample size in cluster-randomized trials with time to event as the primary endpoint

2011

In cluster-randomized trials, groups of individuals (clusters) are randomized to the treatments or interventions to be compared. In many of those trials, the primary objective is to compare the time for an event to occur between randomized groups, and the shared frailty model well fits clustered time-to-event data. Members of the same cluster tend to be more similar than members of different clusters, causing correlations. As correlations affect the power of a trial to detect intervention effects, the clustered design has to be considered in planning the sample size. In this publication, we derive a sample size formula for clustered time-to-event data with constant marginal baseline hazards…

Statistics and ProbabilityTime FactorsEndpoint DeterminationSubstance-Related DisordersEpidemiologyPsychological interventionBiostatisticsTime-to-Treatmentlaw.inventionCorrelationRandom AllocationRandomized controlled triallawStatisticsClinical endpointEconometricsCluster AnalysisHumansPoisson DistributionBaseline (configuration management)Randomized Controlled Trials as TopicMathematicsEvent (probability theory)Likelihood FunctionsModels StatisticalTerm (time)Sample size determinationSample SizeRegression AnalysisSubstance Abuse Treatment CentersStatistics in Medicine
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Structure Learning in Nested Effects Models

2007

Nested Effects Models (NEMs) are a class of graphical models introduced to analyze the results of gene perturbation screens. NEMs explore noisy subset relations between the high-dimensional outputs of phenotyping studies, e.g., the effects showing in gene expression profiles or as morphological features of the perturbed cell. In this paper we expand the statistical basis of NEMs in four directions. First, we derive a new formula for the likelihood function of a NEM, which generalizes previous results for binary data. Second, we prove model identifiability under mild assumptions. Third, we show that the new formulation of the likelihood allows efficiency in traversing model space. Fourth, we…

Statistics and ProbabilityTraverseComputer scienceMolecular Networks (q-bio.MN)Genes MHC Class IIPerturbation (astronomy)Genes InsectFeature selectionQuantitative Biology - Quantitative Methods03 medical and health sciences0302 clinical medicineGeneticsAnimalsheterocyclic compoundsQuantitative Biology - Molecular NetworksGraphical modelMolecular BiologyQuantitative Methods (q-bio.QM)Oligonucleotide Array Sequence Analysis030304 developmental biologyLikelihood Functions0303 health sciencesNanoelectromechanical systemsModels StatisticalModels GeneticGene Expression ProfilingGenomicsComputational MathematicsDrosophila melanogasterPhenotypeFOS: Biological sciencesBinary dataIdentifiabilityRNA InterferenceLikelihood functionAlgorithmAlgorithms030217 neurology & neurosurgery
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A note on alternative parameterizations of a model for evaluating agreement between two tests.

2004

The agreement between two competing tests which purport to measure the same trait is a common concern in test development. In this paper three alternative parameterizations of the measurement model useful in this context are presented. Both one-factor and two-factor approaches are applied. Lord's classic example, where the main problem is to investigate whether time limits represent an extra speed component in a vocabulary test, is used to illustrate the ideas.

Statistics and ProbabilityVocabularyPsychometricsmedia_common.quotation_subjectReproducibility of ResultsContext (language use)General MedicineModels TheoreticalMeasure (mathematics)AgreementTest (assessment)Arts and Humanities (miscellaneous)Component (UML)TraitEconometricsHumansGeneral PsychologyMathematicsmedia_commonThe British journal of mathematical and statistical psychology
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Understanding the determinants of volatility clustering in terms of stationary Markovian processes

2016

Abstract Volatility is a key variable in the modeling of financial markets. The most striking feature of volatility is that it is a long-range correlated stochastic variable, i.e. its autocorrelation function decays like a power-law τ − β for large time lags. In the present work we investigate the determinants of such feature, starting from the empirical observation that the exponent β of a certain stock’s volatility is a linear function of the average correlation of such stock’s volatility with all other volatilities. We propose a simple approach consisting in diagonalizing the cross-correlation matrix of volatilities and investigating whether or not the diagonalized volatilities still kee…

Statistics and ProbabilityVolatility clusteringVolatility Econophysics Long-range correlation Stochastic processes First passage timeStochastic volatilityProbability density functionCondensed Matter PhysicsSABR volatility model01 natural sciencesSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)010305 fluids & plasmasHeston modelFinancial models with long-tailed distributions and volatility clustering0103 physical sciencesForward volatilityEconometricsVolatility (finance)010306 general physicsMathematics
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Main individual and product characteristics influencing in-mouth flavour release during eating masticated food products with different textures: mech…

2013

Research Areas: Life Sciences & Biomedicine - Other Topics; Mathematical & Computational Biology; A mechanistic model predicting flavour release during oral processing of masticated foods was developed. The description of main physiological steps (product mastication and swallowing) and physical mechanisms (mass transfer, product breakdown and dissolution) occurring while eating allowed satisfactory simulation of in vivo release profiles of ethyl propanoate and 2-nonanone, measured by Atmospheric Pressure Chemical Ionization Mass Spectrometry on ten representative subjects during the consumption of four cheeses with different textures. Model sensitivity analysis showed that the main paramet…

Statistics and Probability[ INFO.INFO-MO ] Computer Science [cs]/Modeling and SimulationPhysiology[ SDV.AEN ] Life Sciences [q-bio]/Food and NutritionFlavourAroma compoundMass spectrometryModels BiologicalDynamic modelMass SpectrometryGeneral Biochemistry Genetics and Molecular BiologyEatingchemistry.chemical_compound[SPI]Engineering Sciences [physics]CheeseMass transfer[ SPI ] Engineering Sciences [physics]HumansAroma compoundMass transferFood scienceParticle SizeSalivaMasticationAromaFood oral processing2. Zero hungerMass transfer coefficientMouthGeneral Immunology and MicrobiologybiologyAirApplied MathematicsSaliva ArtificialGeneral MedicineKetonesbiology.organism_classification[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationDeglutitionchemistryFoodTasteModeling and SimulationMasticationDigestionPropionatesBolus (digestion)General Agricultural and Biological Sciences[SDV.AEN]Life Sciences [q-bio]/Food and Nutrition
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Segmented relationships to model erosion of regression effect in Cox regression

2010

In this article we propose a parsimonious parameterisation to model the so-called erosion of the covariate effect in the Cox model, namely a covariate effect approaching to zero as the follow-up time increases. The proposed parameterisation is based on the segmented relationship where proper constraints are set to accomodate for the erosion. Relevant hypothesis testing is discussed. The approach is illustrated on two historical datasets in the survival analysis literature, and some simulation studies are presented to show how the proposed framework leads to a test for a global effect with good power as compared with alternative procedures. Finally, possible generalisations are also present…

Statistics and ProbabilitybreakpointEpidemiologyProportional hazards modelLiver Cirrhosis BiliaryErosion (morphology)Lupus NephritisSet (abstract data type)Segmented regressionHealth Information ManagementNonlinear DynamicsRegression toward the meanCox modelCovariateStatisticsEconometricsHumansComputer SimulationSettore SECS-S/05 - Statistica SocialeSettore SECS-S/01 - Statisticaerosion of effectStatistical hypothesis testingMathematicsFollow-Up StudiesProportional Hazards Models
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cglasso: An R Package for Conditional Graphical Lasso Inference with Censored and Missing Values

2023

Sparse graphical models have revolutionized multivariate inference. With the advent of high-dimensional multivariate data in many applied fields, these methods are able to detect a much lower-dimensional structure, often represented via a sparse conditional independence graph. There have been numerous extensions of such methods in the past decade. Many practical applications have additional covariates or suffer from missing or censored data. Despite the development of these extensions of sparse inference methods for graphical models, there have been so far no implementations for, e.g., conditional graphical models. Here we present the general-purpose package cglasso for estimating sparse co…

Statistics and Probabilityconditional Gaussian graphical modelscglasso conditional Gaussian graphical models glasso high-dimensionality sparsity censoring missing dataglassosparsityhigh-dimensionalityconditional Gaussian graphical models glasso high-dimensionality sparsity censoring missing datacglassomissing datacensoringStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaSoftware
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Bioclimatic atlas of the terrestrial Arctic

2023

AbstractThe Arctic is the region on Earth that is warming at the fastest rate. In addition to rising means of temperature-related variables, Arctic ecosystems are affected by increasingly frequent extreme weather events causing disturbance to Arctic ecosystems. Here, we introduce a new dataset of bioclimatic indices relevant for investigating the changes of Arctic terrestrial ecosystems. The dataset, called ARCLIM, consists of several climate and event-type indices for the northern high-latitude land areas > 45°N. The indices are calculated from the hourly ERA5-Land reanalysis data for 1950–2021 in a spatial grid of 0.1 degree (~9 km) resolution. The indices are provided in three subsets…

Statistics and Probabilityhiilidioksidiarctic regionmeltingclimate changeswarmingPhysiologyEventsrainfallLibrary and Information SciencesklimatologiaEducationeliömaantiedeSnowilmastoSpecies distribution modelsVariabilityClimate-changeclimate1172 Environmental sciencesbiogeographyarktinen aluetemperaturecarbon dioxidesulaminenclimatologyilmastonmuutoksetecosystems (ecology)ekologiaComputer Science Applicationsekosysteemit (ekologia)sademääräclimate changeImpactsSea-icelämpötilaStatistics Probability and UncertaintyTrendslämpeneminenInformation Systemsclimate-change ecology
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