Search results for "Autore"

showing 10 items of 352 documents

Jutekliskās uztveres tematizācija Pētera Handkes stāstā „Senviktuāras kalna mācība”

2015

Bakalaura darbs ir veltīts tēmai „Jutekliskās uztveres tematizācija Pētera Handkes stāstā Senviktuāra kalna mācība”. Darba mērķis ir izmeklēt un aplūkot Pētera Handkes jutekliskās uztveres atspoguļojumu stāstā Senviktuāra kalna mācība. Darba uzdevums ir izpētīt rakstnieka Pētera Handkes personību un viņa slaveno tetraloģiju, it īpaši tetraloģijas otro daļu. Darbs ir sadalīts trijās nodaļās. Pirmajā nodaļā tiek apskatīts un visparēji raksturots jēdziens „mūsdienu literatūra”, kā arī tiek apskatīta tā laika politiskā un sabiedriskā situācija Vācijā un Austrijā. Papildus tiek apskatīta mūsdienu rakstnieku paaudze un Pēters Handke tiek prezentēts kā mūsdienu vācu rakstnieku paaudzes populārs pā…

Erläuterung des Begriffs Gegenwartsliteratur. Charakterisierung der zeitgenössischen Literatur und des Epochenhitergrundes.ValodniecībaBekannte Tetralogie Peter Handkes mit dem Titel Langsame Heimkehr (1979 - 1981); Darstellung der Handlung der drei Erzählungen Langsame Heimkehr Die Lehre der Sainte-Victoire und Kindergeschichte und dem dramatischen Gedicht Über die Dörfer.Thema der Bakkalaureusarbeit lautet „Thematisierung der sinnlichen Wahrnehmung in Peter Handkes Erzählung Die Lehre der Sainte-Victoire“.Übersicht über die Schriftstellergeneration der Gegenwart. Peter Handke als einer der bekanntesten zeitgenössischen deutschsprachigen Autoren; seine Biographie und literariche Entwicklung.Untersuchungsobjekt für diese Arbeit – das 1980 mit einem Vorwort von Karl Krolow herausgegebene Buch von Peter Handke „Die Lehre der Sainte-Victoire“.
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Volatility transmission patterns and terrorist attacks

2009

The objective of this study is to analyze volatility transmission between the US and Eurozone stock markets considering the effects of the September 11, March 11 and July 7 financial crises. In order to do this, we use a multivariate GARCH model and take into account the asymmetric volatility phenomenon, the non-synchronous trading problem and the crises themselves. Moreover, a graphical analysis of the Asymmetric Volatility Impulse-Response Functions (AVIRF) is introduced, which takes into consideration the crisis effect. Results suggest that there is bidirectional and asymmetric volatility transmission and show the different impact that terrorist attacks had on both markets. El objetivo d…

Estadística matemàticaTheorieanwendungtransmissions de volatilitatFinancial economicsEconomicsAutoregressive conditional heteroskedasticitymercados financieros internacionalesMercados financieros internacionales; Crisis financieras; GARCH multivariante; Transmisión de volatilidad. International financial markets; Stock market crisis; Multivariate GARCH; Volatility spillovers.theory applicationMultivariate garch modelOrder (exchange)Volatility swapFinances internacionalsEconomicsEconometricsddc:330multivariate GARCHcrisis del mercado de valorescrisi del mercat de valorsRisk managementInternational financeStock (geology)Economic Statistics Econometrics Business InformaticsMercat Investigacióvolatility spilloversmercats financers internacionalsbusiness.industryinternational financial marketsFinancial marketWirtschaftstock market crisisjel:C32jel:F30Political EconomyMathematical statisticsjel:G15Estadística matemáticaVolatility Modelling Multivariate Volatility GARCH models International Finance International Asset Pricing Risk ManagementVolkswirtschaftslehreTerrorismWirtschaftsstatistik Ökonometrie WirtschaftsinformatikGraphical analysisVolatility (finance)businessVolatility transmissionGeneral Economics Econometrics and FinanceFinancederrames de volatilidad
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Exchange Rate Volatility in the Balkans and Eastern Europe: Implications for International Investments

2016

Our paper’s objective is to study the volatility of exchange rates from the region that have not yet adopted the Euro and are not members of the Exchange Rate Mechanism II by considering the exchange rate regime and the implications of currency volatility for foreign capital flows. We model exchange rate volatility by using standard deviations of daily logarithmic changes in the exchange rates, rolling standard deviations, Hodrick-Prescott filters to detect the trends in volatility and ARIMA models. We find that currency volatility remains a strong issue for these countries and that central banks have attempted to manage it, particularly after the global financial crisis. Spikes in monthly …

Exchange rateCurrencyExchange rate volatilityFinancial crisisBusinessInternational economicsAutoregressive integrated moving averageMonetary economicsVolatility (finance)Exchange-rate regimeStandard deviation
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On the interpretability and computational reliability of frequency-domain Granger causality

2017

This Correspondence article is a comment which directly relates to the paper “A study of problems encountered in Granger causality analysis from a neuroscience perspective” (Stokes and Purdon, 2017). We agree that interpretation issues of Granger causality (GC) in neuroscience exist, partially due to the historically unfortunate use of the name “causality”, as described in previous literature. On the other hand, we think that Stokes and Purdon use a formulation of GC which is outdated (albeit still used) and do not fully account for the potential of the different frequency-domain versions of GC; in doing so, their paper dismisses GC measures based on a suboptimal use of them. Furthermore, s…

FOS: Computer and information sciences0301 basic medicineTheoretical computer scienceImmunology and Microbiology (all)Computer scienceTime series analysiMathematics - Statistics TheoryStatistics Theory (math.ST)Statistics - ApplicationsGeneral Biochemistry Genetics and Molecular BiologyMethodology (stat.ME)Causality (physics)03 medical and health sciences0302 clinical medicinegranger causalityGranger causalityCorrespondenceFOS: MathematicsApplications (stat.AP)Physiological oscillationGeneral Pharmacology Toxicology and PharmaceuticsTime seriessignal processingStatistical Methodologies & Health Informaticsfrequency-domain connectivityReliability (statistics)Statistics - MethodologyInterpretabilityGranger-Geweke causalityBiochemistry Genetics and Molecular Biology (all)Interpretation (logic)General Immunology and Microbiologybrain connectivityGeneral MedicineArticlesvector autoregressive models030104 developmental biologyMathematics and StatisticsWildcardVector autoregressive modelPharmacology Toxicology and Pharmaceutics (all)Frequency domaintime series analysisspectral decompositionSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaBrain connectivity; Directed coherence; Frequency-domain connectivity; Granger-Geweke causality; Physiological oscillations; Spectral decomposition; Time series analysis; Vector autoregressive models; Biochemistry Genetics and Molecular Biology (all); Immunology and Microbiology (all); Pharmacology Toxicology and Pharmaceutics (all)directed coherence030217 neurology & neurosurgeryphysiological oscillations
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Multiscale Information Decomposition: Exact Computation for Multivariate Gaussian Processes

2017

Exploiting the theory of state space models, we derive the exact expressions of the information transfer, as well as redundant and synergistic transfer, for coupled Gaussian processes observed at multiple temporal scales. All of the terms, constituting the frameworks known as interaction information decomposition and partial information decomposition, can thus be analytically obtained for different time scales from the parameters of the VAR model that fits the processes. We report the application of the proposed methodology firstly to benchmark Gaussian systems, showing that this class of systems may generate patterns of information decomposition characterized by prevalently redundant or sy…

FOS: Computer and information sciencesInformation transferComputer scienceGaussianSocial SciencesGeneral Physics and AstronomyInformation theory01 natural sciences010305 fluids & plasmasState spaceStatistical physicslcsh:Scienceinformation theorymultiscale entropylcsh:QC1-999Interaction informationMathematics and Statisticssymbolsinformation dynamicsInformation dynamics; Information transfer; Multiscale entropy; Multivariate time series analysis; Redundancy and synergy; State space models; Vector autoregressive models; Physics and Astronomy (all)information dynamics; information transfer; multiscale entropy; multivariate time series analysis; redundancy and synergy; state space models; vector autoregressive modelsMultivariate time series analysiMathematics - Statistics Theorylcsh:AstrophysicsStatistics Theory (math.ST)Statistics - ApplicationsMethodology (stat.ME)symbols.namesakePhysics and Astronomy (all)0103 physical scienceslcsh:QB460-466FOS: Mathematicsinformation transferRelevance (information retrieval)Applications (stat.AP)Transfer Entropy010306 general physicsGaussian processStatistics - MethodologyState space modelstate space modelsmultivariate time series analysisredundancy and synergyvector autoregressive modelsInformation dynamicVector autoregressive modelSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaTransfer entropylcsh:Qlcsh:PhysicsEntropy
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Local Granger causality

2021

Granger causality is a statistical notion of causal influence based on prediction via vector autoregression. For Gaussian variables it is equivalent to transfer entropy, an information-theoretic measure of time-directed information transfer between jointly dependent processes. We exploit such equivalence and calculate exactly the 'local Granger causality', i.e. the profile of the information transfer at each discrete time point in Gaussian processes; in this frame Granger causality is the average of its local version. Our approach offers a robust and computationally fast method to follow the information transfer along the time history of linear stochastic processes, as well as of nonlinear …

FOS: Computer and information sciencesInformation transferGaussianFOS: Physical sciencestechniques; information theory; granger causalityMachine Learning (stat.ML)Quantitative Biology - Quantitative Methods01 natural sciences010305 fluids & plasmasVector autoregressionsymbols.namesakegranger causalityGranger causalityStatistics - Machine Learning0103 physical sciencesApplied mathematicstime serie010306 general physicsQuantitative Methods (q-bio.QM)Mathematicsinformation theoryStochastic processDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksComputational Physics (physics.comp-ph)Discrete time and continuous timeAutoregressive modelFOS: Biological sciencesSettore ING-INF/06 - Bioingegneria Elettronica E InformaticasymbolsTransfer entropytechniquesPhysics - Computational Physics
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Multiscale analysis of information dynamics for linear multivariate processes.

2016

In the study of complex physical and physiological systems represented by multivariate time series, an issue of great interest is the description of the system dynamics over a range of different temporal scales. While information-theoretic approaches to the multiscale analysis of complex dynamics are being increasingly used, the theoretical properties of the applied measures are poorly understood. This study introduces for the first time a framework for the analytical computation of information dynamics for linear multivariate stochastic processes explored at different time scales. After showing that the multiscale processing of a vector autoregressive (VAR) process introduces a moving aver…

FOS: Computer and information sciencesInformation transferMultivariate statisticsMultivariate analysisComputer scienceComputer Science - Information Theory0206 medical engineeringStochastic ProcesseBiomedical EngineeringFOS: Physical sciencesInformation Storage and RetrievalHealth Informatics02 engineering and technology01 natural sciencesEntropy (classical thermodynamics)Moving average0103 physical sciencesEntropy (information theory)Computer SimulationStatistical physicsEntropy (energy dispersal)Time series010306 general physicsEntropy (arrow of time)Multivariate Analysi1707Stochastic ProcessesEntropy (statistical thermodynamics)Stochastic processInformation Theory (cs.IT)Probability and statisticsModels Theoretical020601 biomedical engineeringComplex dynamicsAutoregressive modelPhysics - Data Analysis Statistics and ProbabilitySignal ProcessingSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaMultivariate AnalysisData Analysis Statistics and Probability (physics.data-an)Entropy (order and disorder)Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
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Conditional particle filters with diffuse initial distributions

2020

Conditional particle filters (CPFs) are powerful smoothing algorithms for general nonlinear/non-Gaussian hidden Markov models. However, CPFs can be inefficient or difficult to apply with diffuse initial distributions, which are common in statistical applications. We propose a simple but generally applicable auxiliary variable method, which can be used together with the CPF in order to perform efficient inference with diffuse initial distributions. The method only requires simulatable Markov transitions that are reversible with respect to the initial distribution, which can be improper. We focus in particular on random-walk type transitions which are reversible with respect to a uniform init…

FOS: Computer and information sciencesStatistics and ProbabilityComputer scienceGaussianBayesian inferenceMarkovin ketjut02 engineering and technology01 natural sciencesStatistics - ComputationArticleTheoretical Computer ScienceMethodology (stat.ME)010104 statistics & probabilitysymbols.namesakeAdaptive Markov chain Monte Carlotilastotiede0202 electrical engineering electronic engineering information engineeringStatistical physics0101 mathematicsDiffuse initialisationHidden Markov modelComputation (stat.CO)Statistics - MethodologyState space modelHidden Markov modelbayesian inferenceMarkov chaindiffuse initialisationbayesilainen menetelmäconditional particle filtersmoothingmatemaattiset menetelmät020206 networking & telecommunicationsConditional particle filterCovariancecompartment modelRandom walkCompartment modelstate space modelComputational Theory and MathematicsAutoregressive modelsymbolsStatistics Probability and UncertaintyParticle filterSmoothingSmoothing
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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
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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
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