Search results for "Time serie"
showing 10 items of 261 documents
Exploring a large dataset : typical behavior of UHF signal propagation
2020
Radioverkon suunnittelua ja käyttöä varten täytyy radio aaltojen eteneminen ymmärtää hyvin. Tässä tutkimuksessa tutustutaan laajaan mittausaineistoon hetkellisiä tehoja maanlaajuisesta UHF verkosta. Spektrianalyysillä todettiin mitatussa tehossa olevan jaksollista vaihtelua taajuuksilla kerran ja kahdesti päivässä. Myös nopeampaa vaihtelua välillä 0:1 mHz ja 1:4 mHz todettiin 34% yhteyksistä. Hierarkisella ryhmittelyllä etsittiin tyypilliset mittausten arvojakaumat. Saaduissa arvojakaumien ryhmissä oli eri levyisiä vasemmalle tai oikealle vinoja tai symmetrisiä jakaumia. The design and operation of radio networks requires good understanding of radio propagation. This study explores a datase…
Economic policy uncertainty effects for forecasting future real economic activity
2018
Recently introduced measures for Economic Policy Uncertainty (EPU) included in the data from 1997 - 2016 have a role in forecasting out-of-sample values for the future real economic activity for both the euro area and the UK economies. The inclusion of EPU measures, either for the US, the UK or for overall European economies, improves the forecasting ability of models based on standard financial market information, especially for the period before the 2008 global crisis. However, during and after the crisis period, the slope of the yield curve and excess stock market returns improves the out-of-sample forecast performance the most compared to an AR-benchmark model. Hence, the EPU informatio…
Land-use changes in an agro-pastoral area (Djougou, Benin) from Landsat archive images (1984 and 2012): a regressive approach combining remote sensin…
2018
Extended abstract:The vegetation of the district of Djougou is affected by large changes due to tree logging, crop field clearing and grazing by increasing numbers of livestock. The dynamics of the landscape is analyzed with a time series of Landsat satellite images (1984-2012). A regressive approach, exploiting the field observations and semi-structured interviews conducted in 2012-2013 in the Bakou-Wewe territory, documents the evolution of land use and facilitates the analysis of Landsat images. An original procedure targets the building of Region of interest (ROIs) for the historic images for which no available field observations exists. The study area is located in central Benin (Plate…
Gap Filling of Biophysical Parameter Time Series with Multi-Output Gaussian Processes
2018
In this work we evaluate multi-output (MO) Gaussian Process (GP) models based on the linear model of coregionalization (LMC) for estimation of biophysical parameter variables under a gap filling setup. In particular, we focus on LAI and fAPAR over rice areas. We show how this problem cannot be solved with standard single-output (SO) GP models, and how the proposed MO-GP models are able to successfully predict these variables even in high missing data regimes, by implicitly performing an across-domain information transfer. CICYT TIN2015-64210-R In this work we evaluate multi-output (MO) Gaussian Process (GP) models based on the linear model of coregionalization (LMC) for estimation of biophy…
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…
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…
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…
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…
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.
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 …