Search results for "Statistic"

showing 10 items of 12520 documents

Autonomy-Supportive and Controlling Styles of Teaching

2015

Autonomy-supportive and controlling styles of teaching are usually considered to be the opposite ends of a single continuum. An alternative view, however, is that individuals can perceive both styles simultaneously, which suggests that they are different constructs ( Bartholomew, Ntoumanis, Ryan, Bosch, & Thøgersen-Ntoumani, 2011 ). Using cluster analysis, Study 1 (N = 160) confirmed that both teaching styles were perceived by students. Four clusters appeared depending on the student’s score on the measures of autonomy and controlling styles (high autonomy–high control; low autonomy–low control; high autonomy–low control; low autonomy–high control). Participants in the high autonomy–lo…

4. Educationmedia_common.quotation_subjectTeaching methodInterpersonal communicationAcademic achievementNeed satisfactionDevelopmental psychologyTeaching stylesIntrinsic motivationPath analysis (statistics)PsychologySocial psychologyGeneral PsychologyAutonomymedia_commonSwiss Journal of Psychology
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GRB 090313 AND THE ORIGIN OF OPTICAL PEAKS IN GAMMA-RAY BURST LIGHT CURVES: IMPLICATIONS FOR LORENTZ FACTORS AND RADIO FLARES

2010

We use a sample of 19 gamma-ray bursts (GRBs) that exhibit single-peaked optical light curves to test the standard fireball model by investigating the relationship between the time of the onset of the afterglow and the temporal rising index. Our sample includes GRBs and X-ray flashes for which we derive a wide range of initial Lorentz factors (40 < Γ < 450). Using plausible model parameters, the typical frequency of the forward shock is expected to lie close to the optical band; within this low typical frequency framework, we use the optical data to constrain εe and show that values derived from the early time light-curve properties are consistent with published typical values derived from …

420Astrophysics::High Energy Astrophysical PhenomenaLorentz transformationgamma-ray burst: generalFOS: Physical sciencesgamma-ray burstAstrophysicsgeneral [gamma-ray burst]Low frequencylaw.inventionsymbols.namesakelawRange (statistics)QDQCQBHigh Energy Astrophysical Phenomena (astro-ph.HE)PhysicsAstronomy and AstrophysicsLight curve420SynchrotronAfterglowShock (mechanics)Space and Planetary SciencesymbolsAstrophysics - High Energy Astrophysical PhenomenaGamma-ray burstThe Astrophysical Journal
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On singular integral and martingale transforms

2007

Linear equivalences of norms of vector-valued singular integral operators and vector-valued martingale transforms are studied. In particular, it is shown that the UMD(p)-constant of a Banach space X equals the norm of the real (or the imaginary) part of the Beurling-Ahlfors singular integral operator, acting on the X-valued L^p-space on the plane. Moreover, replacing equality by a linear equivalence, this is found to be the typical property of even multipliers. A corresponding result for odd multipliers and the Hilbert transform is given.

46B09General Mathematics46B20 (Secondary)Banach space42B15 (Primary) 42B2001 natural sciencesUpper and lower bounds010104 statistics & probabilitysymbols.namesakeCorollary60G46; 42B15 (Primary) 42B20; 46B09; 46B20 (Secondary)Classical Analysis and ODEs (math.CA)FOS: Mathematics60G460101 mathematicsMathematicsNormed vector spaceDiscrete mathematicsApplied MathematicsProbability (math.PR)010102 general mathematicsSingular integralSingular valueMathematics - Classical Analysis and ODEssymbolsHilbert transformMartingale (probability theory)Mathematics - ProbabilityTransactions of the American Mathematical Society
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A Universal Length-Dependent Vibrational Mode in Graphene Nanoribbons

2019

Graphene nanoribbons (GNRs) have attracted considerable interest as their atomically tunable structure makes them promising candidates for future electronic devices. However, obtaining detailed information about the length of GNRs has been challenging and typically relies on low-temperature scanning tunneling microscopy. Such methods are ill-suited for practical device application and characterization. In contrast, Raman spectroscopy is a sensitive method for the characterization of GNRs, in particular for investigating their width and structure. Here, we report on a length-dependent, Raman active low-energy vibrational mode that is present in atomically precise, bottom-up synthesized armch…

530 Physicssubstrate transferSTMFOS: Physical sciencesGeneral Physics and Astronomy02 engineering and technology010402 general chemistryDFT01 natural sciencessymbols.namesakegraphene nanoribbons; Raman spectroscopy; length-dependent mode; STM; substrate transfer; vibrational modes; DFT540 ChemistryMesoscale and Nanoscale Physics (cond-mat.mes-hall)General Materials Sciencevibrational modesCondensed Matter - Materials ScienceCondensed Matter - Mesoscale and Nanoscale Physicsbusiness.industryGeneral EngineeringMode (statistics)Materials Science (cond-mat.mtrl-sci)021001 nanoscience & nanotechnology3. Good health0104 chemical sciencesMolecular vibrationRaman spectroscopysymbols570 Life sciences; biologyOptoelectronicslength-dependent mode0210 nano-technologybusinessRaman spectroscopyGraphene nanoribbonsgraphene nanoribbons
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Constraining Uncertainty in Projected Gross Primary Production With Machine Learning

2020

The terrestrial biosphere is currently slowing down global warming by absorbing about 30% of human emissions of carbon dioxide (CO2). The largest flux of the terrestrial carbon uptake is gross primary production (GPP) defined as the production of carbohydrates by photosynthesis. Elevated atmospheric CO2 concentration is expected to increase GPP (“CO2 fertilization effect”). However, Earth system models (ESMs) exhibit a large range in simulated GPP projections. In this study, we combine an existing emergent constraint on CO2 fertilization with a machine learning approach to constrain the spatial variations of multimodel GPP projections. In a first step, we use observed changes in the CO2 sea…

551.6Atmospheric Science010504 meteorology & atmospheric sciencesComputer scienceSoil ScienceAquatic Science01 natural sciences7. Clean energy010104 statistics & probabilityEconometricsErdsystemmodell -Evaluation und -Analyse[MATH]Mathematics [math]0101 mathematics0105 earth and related environmental sciencesWater Science and TechnologyEcologyEarth System ModelsPaleontologyPrimary productionmodelingForestryGross Primary Production15. Life on landCMIPFuture Climate Projections13. Climate actionEnvironmental scienceJournal of Geophysical Research: Biogeosciences
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Quantization of Poisson Lie Groups and Applications

1996

LetG be a connected Poisson-Lie group. We discuss aspects of the question of Drinfel'd:can G be quantized? and give some answers. WhenG is semisimple (a case where the answer isyes), we introduce quantizable Poisson subalgebras ofC ∞(G), related to harmonic analysis onG; they are a generalization of F.R.T. models of quantum groups, and provide new examples of quantized Poisson algebras.

58B30Pure mathematicsGeneralizationPoisson distribution01 natural sciencesHarmonic analysissymbols.namesakeQuantization (physics)58F060103 physical sciences0101 mathematicsQuantumMathematical PhysicsComputingMilieux_MISCELLANEOUSMathematicsPoisson algebraDiscrete mathematics[MATH.MATH-RT]Mathematics [math]/Representation Theory [math.RT]Group (mathematics)010102 general mathematicsLie groupStatistical and Nonlinear Physics81S1017B37[ MATH.MATH-RT ] Mathematics [math]/Representation Theory [math.RT]symbols010307 mathematical physics16W30
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Rough McKean-Vlasov dynamics for robust ensemble Kalman filtering

2021

Motivated by the challenge of incorporating data into misspecified and multiscale dynamical models, we study a McKean-Vlasov equation that contains the data stream as a common driving rough path. This setting allows us to prove well-posedness as well as continuity with respect to the driver in an appropriate rough-path topology. The latter property is key in our subsequent development of a robust data assimilation methodology: We establish propagation of chaos for the associated interacting particle system, which in turn is suggestive of a numerical scheme that can be viewed as an extension of the ensemble Kalman filter to a rough-path framework. Finally, we discuss a data-driven method bas…

60L20 60L90 60H10 60F99 65C35 62M05Probability (math.PR)FOS: MathematicsMathematics - Statistics TheoryMathematics - Numerical AnalysisNumerical Analysis (math.NA)Statistics Theory (math.ST)Mathematics - Probability
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Inattention and Uncertainty in the Predictive Brain

2021

Negative effects of inattention on task performance can be seen in many contexts of society and human behavior, such as traffic, work, and sports. In traffic, inattention is one of the most frequently cited causal factors in accidents. In order to identify inattention and mitigate its negative effects, there is a need for quantifying attentional demands of dynamic tasks, with a credible basis in cognitive modeling and neuroscience. Recent developments in cognitive science have led to theories of cognition suggesting that brains are an advanced prediction engine. The function of this prediction engine is to support perception and action by continuously matching incoming sensory input with to…

6162 Cognitive sciencecomputational modelingMatching (statistics)Computer sciencemedia_common.quotation_subjectpredictive processingappropriate uncertaintyocclusionTask (project management)03 medical and health sciences0302 clinical medicineNeuroimagingPerceptiondrivingRC346-429Function (engineering)tarkkaavaisuusennakointi030304 developmental biologymedia_common0303 health sciencesCognitionkognitiiviset prosessitepävarmuusautoilijatAction (philosophy)NormativeNeurology. Diseases of the nervous system030217 neurology & neurosurgeryCognitive psychology
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Separation of uncorrelated stationary time series using autocovariance matrices

2014

Blind source separation (BSS) is a signal processing tool, which is widely used in various fields. Examples include biomedical signal separation, brain imaging and economic time series applications. In BSS, one assumes that the observed $p$ time series are linear combinations of $p$ latent uncorrelated weakly stationary time series. The aim is then to find an estimate for an unmixing matrix, which transforms the observed time series back to uncorrelated latent time series. In SOBI (Second Order Blind Identification) joint diagonalization of the covariance matrix and autocovariance matrices with several lags is used to estimate the unmixing matrix. The rows of an unmixing matrix can be deriv…

62H05 62H10Asymptotic Normality ; Blind Source Separation ; Joint Diagonalization ; Linear Process ; SobiFOS: MathematicsMathematics - Statistics TheoryStatistics Theory (math.ST)
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On the stability of some controlled Markov chains and its applications to stochastic approximation with Markovian dynamic

2015

We develop a practical approach to establish the stability, that is, the recurrence in a given set, of a large class of controlled Markov chains. These processes arise in various areas of applied science and encompass important numerical methods. We show in particular how individual Lyapunov functions and associated drift conditions for the parametrized family of Markov transition probabilities and the parameter update can be combined to form Lyapunov functions for the joint process, leading to the proof of the desired stability property. Of particular interest is the fact that the approach applies even in situations where the two components of the process present a time-scale separation, w…

65C05FOS: Computer and information sciencesStatistics and ProbabilityLyapunov functionStability (learning theory)Markov processContext (language use)Mathematics - Statistics Theorycontrolled Markov chainsStatistics Theory (math.ST)Stochastic approximation01 natural sciencesMethodology (stat.ME)010104 statistics & probabilitysymbols.namesake60J05stochastic approximationFOS: MathematicsComputational statisticsApplied mathematics60J220101 mathematicsStatistics - MethodologyMathematicsSequenceMarkov chain010102 general mathematicsStability Markov chainssymbolsStatistics Probability and Uncertaintyadaptive Markov chain Monte Carlo
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