Search results for " Time"

showing 10 items of 3005 documents

Corrigendum: ExGUtils: A Python Package for Statistical Analysis With the ex-Gaussian Probability Density

2018

The study of reaction times and their underlying cognitive processes is an important field in Psychology. Reaction times are usually modeled through the ex-Gaussian distribution, because it provides a good fit to multiple empirical data. The complexity of this distribution makes the use of computational tools an essential element in the field. Therefore, there is a strong need for efficient and versatile computational tools for the research in this area. In this manuscript we discuss some mathematical details of the ex-Gaussian distribution and apply the ExGUtils package, a set of functions and numerical tools, programmed for python, developed for numerical analysis of data involving the ex…

FOS: Computer and information sciencesResponse timeslcsh:BF1-990Probability density functionex-Gaussian fitStatistics - Applications050105 experimental psychology03 medical and health sciences0302 clinical medicineSignificance testingresponse componentsConceptual AnalysisPsychology0501 psychology and cognitive sciencesStatistical analysisApplications (stat.AP)Ex-Gaussian fitTempo de reaçãoGeneral Psychologycomputer.programming_languagesignificance testingResponse componentsNumerical analysis05 social sciencesAnálise estatísticaCorrectionPython (programming language)Ex gaussianDistribuição Gaussianapythonlcsh:PsychologyOutlierTrimmingPsychologyMATEMATICA APLICADAAlgorithmcomputerSignificance testing030217 neurology & neurosurgeryresponse timesPython
researchProduct

Mixture Hidden Markov Models for Sequence Data: The seqHMM Package in R

2019

Sequence analysis is being more and more widely used for the analysis of social sequences and other multivariate categorical time series data. However, it is often complex to describe, visualize, and compare large sequence data, especially when there are multiple parallel sequences per subject. Hidden (latent) Markov models (HMMs) are able to detect underlying latent structures and they can be used in various longitudinal settings: to account for measurement error, to detect unobservable states, or to compress information across several types of observations. Extending to mixture hidden Markov models (MHMMs) allows clustering data into homogeneous subsets, with or without external covariate…

FOS: Computer and information sciencesStatistics and ProbabilityMultivariate statisticssequence analysisaikasarjatComputer sciencerMarkov modelStatistics - ComputationStatistics - Applications01 natural sciencesUnobservablecategorical time seriesR-kieli010104 statistics & probabilitymulti-channel sequences; categorical time series; visualizing sequence data; visualizing models; latent Markov models; latent class models; RCovariateApplications (stat.AP)Sannolikhetsteori och statistikComputer software0101 mathematicsTime seriesProbability Theory and StatisticsHidden Markov modelCluster analysislcsh:Statisticslcsh:HA1-4737Categorical variableComputation (stat.CO)ta112business.industryvisualizing sequence dataR (programming languages)Pattern recognitionmulti-channel sequencesvisualizing modelslatent class modelssekvenssianalyysiArtificial intelligencelatent markov modelstime seriesStatistics Probability and UncertaintybusinessSoftwareJournal of Statistical Software
researchProduct

An ensemble approach to short-term forecast of COVID-19 intensive care occupancy in Italian Regions

2020

Abstract The availability of intensive care beds during the COVID‐19 epidemic is crucial to guarantee the best possible treatment to severely affected patients. In this work we show a simple strategy for short‐term prediction of COVID‐19 intensive care unit (ICU) beds, that has proved very effective during the Italian outbreak in February to May 2020. Our approach is based on an optimal ensemble of two simple methods: a generalized linear mixed regression model, which pools information over different areas, and an area‐specific nonstationary integer autoregressive methodology. Optimal weights are estimated using a leave‐last‐out rationale. The approach has been set up and validated during t…

FOS: Computer and information sciencesStatistics and ProbabilityTime FactorsOccupancyCoronavirus disease 2019 (COVID-19)Computer science01 natural sciencesGeneralized linear mixed modelSARS‐CoV‐2law.inventionclustered data; COVID-19; generalized linear mixed model; integer autoregressive; integer autoregressive model; panel data; SARS-CoV-2; weighted ensembleMethodology (stat.ME)panel data010104 statistics & probability03 medical and health sciences0302 clinical medicinelawCOVID‐19Intensive careEconometricsHumansclustered data030212 general & internal medicine0101 mathematicsPandemicsStatistics - MethodologySARS-CoV-2Reproducibility of ResultsCOVID-19General Medicineweighted ensembleIntensive care unitResearch PapersTerm (time)integer autoregressiveIntensive Care UnitsAutoregressive modelItalyNonlinear Dynamicsgeneralized linear mixed modelinteger autoregressive modelclustered data; COVID-19; generalized linear mixed model; integer autoregressive; integer autoregressive model; panel data; SARS-CoV-2; weighted ensemble; COVID-19; Humans; Intensive Care Units; Italy; Nonlinear Dynamics; Pandemics; Reproducibility of Results; Time Factors; ForecastingStatistics Probability and UncertaintySettore SECS-S/01Settore SECS-S/01 - StatisticaPanel dataResearch PaperForecasting
researchProduct

KFAS : Exponential Family State Space Models in R

2017

State space modelling is an efficient and flexible method for statistical inference of a broad class of time series and other data. This paper describes an R package KFAS for state space modelling with the observations from an exponential family, namely Gaussian, Poisson, binomial, negative binomial and gamma distributions. After introducing the basic theory behind Gaussian and non-Gaussian state space models, an illustrative example of Poisson time series forecasting is provided. Finally, a comparison to alternative R packages suitable for non-Gaussian time series modelling is presented.

FOS: Computer and information sciencesStatistics and ProbabilityaikasarjatGaussianNegative binomial distributionforecastingPoisson distribution01 natural sciencesStatistics - ComputationMethodology (stat.ME)010104 statistics & probability03 medical and health sciencessymbols.namesake0302 clinical medicineExponential familyexponential familyGamma distributionStatistical inferenceState spaceApplied mathematicsSannolikhetsteori och statistik030212 general & internal medicine0101 mathematicsProbability Theory and Statisticslcsh:Statisticslcsh:HA1-4737Computation (stat.CO)Statistics - MethodologyMathematicsR; exponential family; state space models; time series; forecasting; dynamic linear modelsta112state space modelsSeries (mathematics)RStatistics; Computer softwaresymbolsStatistics Probability and Uncertaintytime seriesSoftwaredynamic linear models
researchProduct

Reliability analysis of processes with moving cracked material

2015

Abstract The reliability of processes with moving elastic and isotropic material containing initial cracks is considered in terms of fracture. The material is modelled as a moving plate which is simply supported from two of its sides and subjected to homogeneous tension acting in the travelling direction. For tension, two models are studied: (i) tension is constant with respect to time, and (ii) tension varies temporally according to an Ornstein–Uhlenbeck process. Cracks of random length are assumed to occur in the material according to a stochastic counting process. For a general counting process, a representation of the nonfracture probability of the system is obtained that exploits condi…

FOS: Computer and information sciencesStochastic modellingBoundary (topology)02 engineering and technologyComputational Engineering Finance and Science (cs.CE)0203 mechanical engineeringfirst passage timeComputer Science - Computational Engineering Finance and Sciencestochastic modelMathematics040101 forestryta214Counting processTension (physics)Applied Mathematicsta111Mathematical analysisIsotropyOrnstein–Uhlenbeck process04 agricultural and veterinary sciencesmoving material020303 mechanical engineering & transportsfractureModeling and Simulation0401 agriculture forestry and fisheriesOrnstein-Uhlenbeck processFirst-hitting-time modelConstant (mathematics)Applied Mathematical Modelling
researchProduct

Multiscale partial information decomposition of dynamic processes with short and long-range correlations: theory and application to cardiovascular co…

2022

Abstract Objective. In this work, an analytical framework for the multiscale analysis of multivariate Gaussian processes is presented, whereby the computation of Partial Information Decomposition measures is achieved accounting for the simultaneous presence of short-term dynamics and long-range correlations. Approach. We consider physiological time series mapping the activity of the cardiac, vascular and respiratory systems in the field of Network Physiology. In this context, the multiscale representation of transfer entropy within the network of interactions among Systolic arterial pressure (S), respiration (R) and heart period (H), as well as the decomposition into unique, redundant and s…

FOS: Computer and information sciencesmultivariate time seriesPhysiologyEntropyRespirationBiomedical EngineeringBiophysicsheart rate variabilitytransfer entropyredundancy and synergyBlood PressureHeartQuantitative Biology - Quantitative MethodsCardiovascular SystemMethodology (stat.ME)Heart RatePhysiology (medical)FOS: Biological sciencesCardiovascular controlSettore ING-INF/06 - Bioingegneria Elettronica E Informaticavector autoregressive fractionally integrated (VARFI) modelsHumansQuantitative Methods (q-bio.QM)Statistics - MethodologyPhysiological measurement
researchProduct

Using the Scaling Analysis to Characterize Financial Markets

2003

We empirically analyze the scaling properties of daily Foreign Exchange rates, Stock Market indices and Bond futures across different financial markets. We study the scaling behaviour of the time series by using a generalized Hurst exponent approach. We verify the robustness of this approach and we compare the results with the scaling properties in the frequency-domain. We find evidence of deviations from the pure Brownian motion behavior. We show that these deviations are associated with characteristics of the specific markets and they can be, therefore, used to distinguish the different degrees of development of the markets.

FOS: Economics and businessStatistical Finance (q-fin.ST)Statistical Mechanics (cond-mat.stat-mech)jel:G1Quantitative Finance - Statistical FinanceFOS: Physical sciencesCondensed Matter - Statistical Mechanicsscaling exponents time series analysis multi-fractals financial market
researchProduct

Effects of Nest and Colony Features on Lesser Kestrel (Falco naumanni) Reproductive Success

2012

The Lesser Kestrel is a facultative colonial raptor mostly breeding in man-made structures. During 2009-2011 we checked the fate of 545 nests found in 18 colonies located in south-eastern Sicily. We determined the reproductive success of breeding pairs by analysing the survival time of each egg to hatching ( n = 2,495) and each nestling to fledging ( n = 1,849) with the linear hazard model of survival times. We determined whether egg and nestling survival differed between years with a Gehan–Wilcoxon test. By Cox regressions, we related the survival times with nest and colony features. Egg and nestling survival times showed a strong annual effect. The two reproductive stages of the Lesser K…

FacultativebiologyNestReproductive successSettore BIO/05 - ZoologiaFalco naumanniZoologyAnimal Science and ZoologyKestrelbiology.organism_classificationsurvival time analysis egg survival nestling survival lesser kestrel Falco naumanni steppeland birdsEcology Evolution Behavior and SystematicsAvian Biology Research
researchProduct

El hombre unidimensional fragmentado

2013

Parafraseamos el título del conocido ensayo de Herbert Marcuse, puesto que la imagen que tradicionalmente se ha generado del hombre, de la masculinidad, ha sido unidimensional. Es decir, el hombre se caracterizaba por unos rasgos y conductas establecidos y afianzados desde tiempos remotos, considerándose todas las demás señas diferenciadoras como meras desviaciones impropias de lo normativo. Pero observaremos que esta realidad incuestionable, tal y como han analizado diversos investigadores a través de lo que se ha venido en denominar Men’s studies, ha demostrado ser una falacia difícil de mantener a lo largo de la historia y que en la actualidad deviene en falaz e inoperante frente a los c…

Fallacymujer:ANTROPOLOGÍA [UNESCO]dominaciónmedia_common.quotation_subjectAncient timeUNESCO::ANTROPOLOGÍAGender studiesmodeloParaphrasemasculinidaddeconstrucciónEpistemologySociologiaMasculinityIgualtatGeneral Earth and Planetary SciencesNormativeSociologyGeneral Environmental Sciencemedia_common
researchProduct

Characterization of protofibrillar aggregates of bovine serum albumin by tryptophans fluorescence lifetime

2010

We report an experimental study on the thermally induced aggregation of Bovine Serum Albumin at basic pH. In these conditions, we observe the growth of simple protofibrillar structures via the formation of intermolecular beta-sheets promoted by the increased electrostatic repulsion. Here we present a study on the time resolved fluorescence of Tryptophans (Trp) along the aggregation kinetics in the above reported conditions. We use the lifetimes distribution approach as a useful tool for the interpretation of the fluorescence decay in terms of protein conformational substates and interconversion dynamics. Trp fluorescence lifetime depends from protein conformations, also in relation with sol…

Fibril Time resolve fluorescence AggregationSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)
researchProduct