Search results for "time series"

showing 7 items of 247 documents

An Examination of Tourist Arrivals Dynamics Using Short-Term Time Series Data: A Space—Time Cluster Approach

2013

The purpose of this study is to examine the development of Italian tourist areas ( circoscrizioni turistiche) through a cluster analysis of short time series. The technique is an adaptation of the functional data analysis approach developed by Abraham et al (2003), which combines spline interpolation with k-means clustering. The findings indicate the presence of two patterns (increasing and stable) averagely characterizing groups of territories. Moreover, tests of spatial contiguity suggest the presence of ‘space–time clusters’; that is, areas in the same ‘time cluster’ are also spatially contiguous. These findings appear to be more robust in particular for those series characterized by an…

spline interpolationjoin count testSeries (mathematics)Computer scienceSpace timeGeography Planning and Developmentk-means clusteringcluster analysis; short time series; spline interpolation; K-means; join count test; Italian tourist areasFunctional data analysisjel:C21jel:C22jel:C38jel:C14jel:L83K-meanshort time serieContiguity (probability theory)Tourism Leisure and Hospitality Managementcluster analysiItalian tourist areasEconometricsCluster (physics)Settore SECS-S/05 - Statistica SocialeSpline interpolationCluster analysisTourism Economics
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Inferring directionality of coupled dynamical systems using Gaussian process priors: Application on neurovascular systems

2022

Dynamical system theory has recently shown promise for uncovering causality and directionality in complex systems, particularly using the method of convergent cross mapping (CCM). In spite of its success in the literature, the presence of process noise raises concern about CCM's ability to uncover coupling direction. Furthermore, CCM's capacity to detect indirect causal links may be challenged in simulated unidrectionally coupled Rossler-Lorenz systems. To overcome these limitations, we propose a method that places a Gaussian process prior on a cross mapping function (named GP-CCM) to impose constraints on local state space neighborhood comparisons. Bayesian posterior likelihood and…

stochastic analysis methodsstatistical physicsneuronal dynamics01 natural sciencesCausality03 medical and health sciencesnonlinear dynamics0302 clinical medicinephase space methodstime series analysis0103 physical sciencesSettore ING-INF/06 - Bioingegneria Elettronica E Informaticabiological physics010306 general physics030217 neurology & neurosurgeryinformation theoryPhysical Review E
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Comment améliorer la prévision des ventes pour le marketing ? Les apports de la théorie du chaos

2013

La littérature en marketing constate un décalage entre les avancées réalisées par les chercheurs qui développent de nouvelles méthodes de prévision des ventes, et l'usage massif de méthodes traditionnelles reposant sur l'hypothèse de linéarité des processus analysés. Cette recherche expose la contribution potentielle de la théorie du chaos à l'amélioration de la prévision des ventes. Une illustration de ces apports est proposée avec une application à la prévision des ventes de consoles de jeux vidéo au Japon. Les résultats mettent en évidence la capacité de la méthode proposée à détecter la présence de chaos dans la série et montrent la possibilité de préciser l'horizon de prévisibilité des…

séries chronologiques Sales forecasting[SHS.STAT] Humanities and Social Sciences/Methods and statisticschaos theorythéorie du chaostime series[SHS.GESTION] Humanities and Social Sciences/Business administrationPrévision des ventes
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How news affect the trading behavior of different categories of investors in a financial market

2015

We investigate the trading behavior of a large set of single investors trading the highly liquid Nokia stock over the period 2003-2008 with the aim of determining the relative role of endogenous and exogenous factors that may affect their behavior. As endogenous factors we consider returns and volatility, whereas the exogenous factors we use are the total daily number of news and a semantic variable based on a sentiment analysis of news. Linear regression and partial correlation analysis of data show that different categories of investors are differently correlated to these factors. Governmental and non profit organizations are weakly sensitive to news and returns or volatility, and, typica…

ta511Statistical Finance (q-fin.ST)Endogenous Factorsta114Sentiment analysisFinancial marketQuantitative Finance - Statistical FinanceNon profitFinancial marketInvestor behaviourSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Heterogeneity of agentFOS: Economics and businessSettore SECS-S/06 -Metodi Mat. dell'Economia e d. Scienze Attuariali e Finanz.Linear regressionEconometricsEconomicsVolatility (finance)Explanatory powerInformation in capital marketGeneral Economics Econometrics and FinanceFinanceStock (geology)health care economics and organizationsEmpirical time series analysis
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Qualitative analysis of housing demand using Google trends data

2019

Big data analytics often refer to the breakdown of huge amounts of data into a more readable and useful format. This study utilises Google Trends big data as a proxy for an analysis of housing demand. We employ a qualitative method (fuzzy set/Qualitative Comparative Analysis, fsQCA), instead of a quantitative method, for our estimate and forecast. The empirical results show that fsQCA successfully forecasts seasonal time series, even though the dataset is small in size. Our findings fill the gap in the qualitative and time series forecasting literature, and the forecasting procedure herein also offers a good standard for industry.

time series modelshousing demandEconomics and Econometricsbusiness.industryComputer scienceSèries temporals AnàlisiBig datalcsh:Regional economics. Space in economicsData sciencelcsh:HD72-88lcsh:HT388Proxy (climate)lcsh:Economic growth development planningQualitative analysisTime series models; qualitative forecasting; housing demandbusinessqualitative forecastingEconomic Research-Ekonomska Istraživanja
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Identifying the Sales Patterns of Online Stores with Time Series Clustering

2018

Electronic commerce, especially in the business-to-consumer (B2C) context, has for years been a popular research topic in information systems (IS). However, the prior research on the topic has traditionally been dominated by the consumer focus instead of the business focus of online stores. For example, whereas various segmentations exist for online consumers based on their purchase behaviour, no such segmentations have been developed for online stores based on their sales patterns. In this study, our objective is to address this gap in prior research by identifying the most typical sales patterns of online stores operating in the B2C context. By using self-organising maps (SOM) to analyse …

verkkokauppa (verkkoliiketoiminta)Series (mathematics)Computer scienceverkkokauppabusiness-to-consumercomputer.software_genreB2Conline storesklusteritsegmentointisales patternsSegmentationData miningCluster analysiscomputertime series clustering
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Univariate and multivariate properties of wind velocity time series

2009

We analyze the time series of hourly average wind speeds measured at 29 different stations located in Sicily, a region with a complex morphology. The investigation, performed from the univariate as well as the multivariate point of view, evidences that the statistical properties of wind at the single sites have features that are not reproduced by standard models and, thus, require specific modeling. Moreover, the synchronous evolution of wind velocity presents a cluster structure, obtained with different algorithms, that persists in the standard deviation too.

wind velocity time seriesStatistics and ProbabilityMultivariate statisticsSeries (mathematics)MeteorologyUnivariateStatistical and Nonlinear PhysicsStandard deviationWind speedhydrodynamic fluctuations random graphs networksLog wind profilePoint (geometry)Statistics Probability and UncertaintyMathematics
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