Academic literature on the topic 'Analyse en séries temporelles'
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Journal articles on the topic "Analyse en séries temporelles"
Czernichow, Thomas, Bernadette Dorizzi, and Antonio Muñoz San Roque. "Sélection de variables et séries temporelles par analyse statistique des sensibilités." Revue d'intelligence artificielle 15, no. 3-4 (December 1, 2001): 411–27. http://dx.doi.org/10.3166/ria.15.411-427.
Full textAires, Filipe, Alain Chédin, and Jean-Pierre Nadal. "Analyse de séries temporelles géophysiques et théorie de l'information: L'analyse en composantes indépendantes." Comptes Rendus de l'Académie des Sciences - Series IIA - Earth and Planetary Science 328, no. 9 (May 1999): 569–75. http://dx.doi.org/10.1016/s1251-8050(99)80152-9.
Full textBec, Frédérique. "Impulsions dominantes et analyse des fluctuations de l’économie française." Articles 70, no. 1 (March 23, 2009): 5–26. http://dx.doi.org/10.7202/602127ar.
Full textGharbi, M., P. Quénel, S. Cassadou, and L. Marrama. "Analyse des séries temporelles de la dengue en Guadeloupe en fonction du climat : modèles prédictifs." Revue d'Épidémiologie et de Santé Publique 58 (September 2010): S92. http://dx.doi.org/10.1016/j.respe.2010.06.143.
Full textEl-Jabi, N., G. Le-Kourdahi, and D. Caissie. "Modélisation stochastique de la température de l'eau en rivière." Revue des sciences de l'eau 8, no. 1 (April 12, 2005): 77–95. http://dx.doi.org/10.7202/705214ar.
Full textAmalaman, Marc Auriol, Gil Mahé, Béh Ibrahim Diomande, Armand Zamblé Tra Bi, Nathalie Rouché, Zeineddine Nouaceur, and Benoit Laignel. "Analyse en ondelettes des séries temporelles aux stations de pluies et débits dans le bassin versant de Tortiya amont (Nord de la Côte d'Ivoire)." Proceedings of IAHS 385 (April 19, 2024): 365–70. http://dx.doi.org/10.5194/piahs-385-365-2024.
Full textSoatiana, R., L. Randrianasolo, J. M. Heraud, L. Ravalolomanana, A. Randrianarivo, and V. Richard. "Tendances saisonnières de la grippe à Madagascar. Analyse des séries temporelles des données de surveillance sentinelle." Revue d'Épidémiologie et de Santé Publique 58 (September 2010): S89. http://dx.doi.org/10.1016/j.respe.2010.06.134.
Full textSOMÉ, Yélézouomin Stéphane Corentin, Alimata ZOROM, Wièmè SOMÉ, and Pounyala Awa OUOBA. "Analyse de la dynamique de la végétation du Burkina Faso par utilisation de séries temporelles d’images FAPAR." International Journal of Progressive Sciences and Technologies 38, no. 1 (April 27, 2023): 287. http://dx.doi.org/10.52155/ijpsat.v38.1.5191.
Full textBloch, Laurence, Pierre-Yves Hénin, Olivier Marchand, F. Meunier, and Claude Thélot. "Analyse macro-économique des taux d’activité et flexion conjoncturelle." Économie appliquée 39, no. 4 (1986): 665–703. http://dx.doi.org/10.3406/ecoap.1986.4098.
Full textGarcía-Perez, Miguel A. "La décennie 1989-1999 dans la psychologie espagnole : analyse de la recherche en statistiques, méthodologie et théorie psychométrique." Bulletin de psychologie 56, no. 464 (2003): 167–78. http://dx.doi.org/10.3406/bupsy.2003.15211.
Full textDissertations / Theses on the topic "Analyse en séries temporelles"
Le, Tertre Alain. "Séries temporelles et analyse combinée des liens pollution atmosphérique et santé." Paris 6, 2005. http://www.theses.fr/2005PA066434.
Full textToque, Carole. "Pour l'identification de modèles factoriels de séries temporelles : application aux ARMA stationnaires." Phd thesis, Télécom ParisTech, 2006. http://pastel.archives-ouvertes.fr/pastel-00001966.
Full textDesrosiers, Maxime. "Le prix du risque idiosyncrasique : une analyse en séries temporelles et coupe transversale." Master's thesis, Université Laval, 2020. http://hdl.handle.net/20.500.11794/67076.
Full textDesrues, Mathilde. "Surveillance opérationnelle de mouvements gravitaires par séries temporelles d'images." Thesis, Strasbourg, 2021. http://www.theses.fr/2021STRAH002.
Full textUnderstanding the dynamics and the behavior of gravitational slope movements is essential to anticipate catastrophic failures and thus to protect lives and infrastructures. Several geodetic techniques already bring some information on the displacement / deformation fields of the unstable slopes. These techniques allow the analysis of the geometrical properties of the moving masses and of the mechanical behavior of the slopes. By combining time series of passive terrestrial imagery and these classical techniques, the amount of collected information is densified and spatially distributed. Digital passive sensors are increasingly used for the detection and the monitoring of gravitational motion. They provide both qualitative information, such as the detection of surface changes, and a quantitative characterization, such as the quantification of the soil displacement by correlation techniques. Our approach consists in analyzing time series of terrestrial images from either a single fixed camera or pair-wise cameras, the latter to obtain redundant and additional information. The time series are processed to detect the areas in which the Kinematic behavior is homogeneous. The slope properties, such as the sliding volume and the thickness of the moving mass, are part of the analysis results to obtain an overview which is as complete as possible. This work is presented around the analysis of four landslides located in the French Alps. It is part of a CIFRE/ANRT agreement between the SAGE Society - Société Alpine de Géotechnique (Gières, France) and the IPGS - Institut de Physique du Globe de Strasbourg / CNRS UMR 7516 (Strasbourg, France)
Ben, othmane Zied. "Analyse et visualisation pour l'étude de la qualité des séries temporelles de données imparfaites." Thesis, Reims, 2020. http://www.theses.fr/2020REIMS002.
Full textThis thesis focuses on the quality of the information collected by sensors on the web. These data form time series that are incomplete, imprecise, and are on quantitative scales that are not very comparable. In this context, we are particularly interested in the variability and stability of these time series. We propose two approaches to quantify them. The first is based on a representation using quantiles, the second is a fuzzy approach. Using these indicators, we propose an interactive visualization tool dedicated to the analysis of the quality of the harvest carried out by the sensors. This work is part of a CIFRE collaboration with Kantar
Owusu, Patrick Asante. "Modélisation de dépendances dans des séries temporelles co-évolutives." Electronic Thesis or Diss., Université de Lorraine, 2024. http://www.theses.fr/2024LORR0104.
Full textCurrent research in time series analysis shows that there are insufficient formal approaches for modelling the dependencies of multiple or co-evolving time series as they change over time. In this dissertation, we develop a formal approach for analysing the temporality and evolution of dependencies via the definitions of sub-time series, where a sub-time series is a segment of the original time series data. In general, we design an approach based on the principle of sliding windows to analyse the temporal nature and dependency changes between evolving time series. More precisely, each sub-time series is analysed independently to understand the local dependencies and how these dependencies shift as the window moves forward in time. This, therefore, allows us to model the temporal evolution of dependencies with finer granularity. Our contributions relating to the modelling of dependencies highlight the significance of understanding the dynamic interconnections between multiple time series that evolve together over time. The primary objective is to develop robust techniques to effectively capture these evolving dependencies, thereby improving the analysis and prediction of complex systems such as financial markets, climate systems, and other domains generating voluminous time series data. The dissertation explores the use of autoregressive models and proposes novel methods for identifying and modelling these dependencies, addressing the limitations of traditional methods that often overlook the temporal dynamics and scalability required for handling large datasets. A core aspect of the research is the development of a two-step approach to detect and model evolving effects in multiple time series. The first step involves identifying patterns to recreate series variations over various time intervals using finite linear models. This step is crucial for capturing the temporal dependencies within the data. By leveraging a sequence of bipartite graphs, the study models change across multiple time series, linking repetitive and new dependencies at varying time durations in sub-series. This approach not only simplifies the process of identifying dependencies but also provides a scalable solution for analysing large datasets, as demonstrated through experiments with, for example, real-world financial market data. The dissertation further emphasises the importance of interpretability in modelling co-evolving time series. By integrating large language models (LLMs) and context-aware techniques, the research enhances the understanding of the underlying factors driving changes in time series data. This interpretability is achieved through the construction of temporal graphs and the serialisation of these graphs into natural language, providing clear and comprehensive insights into the dependencies and interactions within the data. The combination of autoregressive models and LLMs enables the generation of plausible and interpretable predictions, making the approach suitable for real-world applications where trust and clarity in model outputs are paramount
Ladjouze, Salim. "Problèmes d'estimation dans les séries temporelles stationnaires avec données manquantes." Phd thesis, Université Joseph Fourier (Grenoble ; 1971-2015), 1986. http://tel.archives-ouvertes.fr/tel-00319946.
Full textAchouch, Ayman. "Analyse économétrique des prix des métaux : une application multivariée des méthodes statistiques aux séries temporelles." Montpellier 1, 1998. http://www.theses.fr/1998MON10025.
Full textHéas, Patrick. "Apprentissage bayésien de structures spatio-temporelles : application à la fouille visuelle de séries temporelles d'images de satellites." Toulouse, ENSAE, 2005. http://www.theses.fr/2005ESAE0004.
Full textBoulin, Alexis. "Partitionnement des variables de séries temporelles multivariées selon la dépendance de leurs extrêmes." Electronic Thesis or Diss., Université Côte d'Azur, 2024. http://www.theses.fr/2024COAZ5039.
Full textIn a wide range of applications, from climate science to finance, extreme events with a non-negligible probability can occur, leading to disastrous consequences. Extremes in climatic events such as wind, temperature, and precipitation can profoundly impact humans and ecosystems, resulting in events like floods, landslides, or heatwaves. When the focus is on studying variables measured over time at numerous specific locations, such as the previously mentioned variables, partitioning these variables becomes essential to summarize and visualize spatial trends, which is crucial in the study of extreme events. This thesis explores several models and methods for partitioning the variables of a multivariate stationary process, focusing on extreme dependencies.Chapter 1 introduces the concepts of modeling dependence through copulas, which are fundamental for extreme dependence. The notion of regular variation, essential for studying extremes, is introduced, and weakly dependent processes are discussed. Partitioning is examined through the paradigms of separation-proximity and model-based clustering. Non-asymptotic analysis is also addressed to evaluate our methods in fixed dimensions.Chapter 2 study the dependence between maximum values is crucial for risk analysis. Using the extreme value copula function and the madogram, this chapter focuses on non-parametric estimation with missing data. A functional central limit theorem is established, demonstrating the convergence of the madogram to a tight Gaussian process. Formulas for asymptotic variance are presented, illustrated by a numerical study.Chapter 3 proposes asymptotically independent block (AI-block) models for partitioning variables, defining clusters based on the independence of maxima. An algorithm is introduced to recover clusters without specifying their number in advance. Theoretical efficiency of the algorithm is demonstrated, and a data-driven parameter selection method is proposed. The method is applied to neuroscience and environmental data, showcasing its potential.Chapter 4 adapts partitioning techniques to analyze composite extreme events in European climate data. Sub-regions with dependencies in extreme precipitation and wind speed are identified using ERA5 data from 1979 to 2022. The obtained clusters are spatially concentrated, offering a deep understanding of the regional distribution of extremes. The proposed methods efficiently reduce data size while extracting critical information on extreme events.Chapter 5 proposes a new estimation method for matrices in a latent factor linear model, where each component of a random vector is expressed by a linear equation with factors and noise. Unlike classical approaches based on joint normality, we assume factors are distributed according to standard Fréchet distributions, allowing a better description of extreme dependence. An estimation method is proposed, ensuring a unique solution under certain conditions. An adaptive upper bound for the estimator is provided, adaptable to dimension and the number of factors
Books on the topic "Analyse en séries temporelles"
Meuriot, Véronique. Une histoire des concepts des séries temporelles. Louvain-la-Neuve: Harmattan-Academia, 2012.
Find full textAugustín, Maravall, Sánchez Fernando J, and Banco de España. Servicio de Estudios, eds. Program TSW reference manual. Madrid: Banco de España, 2001.
Find full textBouopda, Pierre Eugène. Analyse des séries temporelles: Une application à la modélisation macroéconomique des comportements bancaires dans le cas français. Grenoble: A.N.R.T, Université Pierre Mendes France (Grenoble II), 1992.
Find full textPawłowski, Adam. Séries temporelles en linguistique: Avec application à l'attribution de textes, Romain Gary et Emile Ajar. Paris: H. Champion, 1998.
Find full textBac, Catherine. Saisonnalité et non stationnarité: Une analyse en termes de séries temporelles avec applications à la boucle prix salaire et à la dynamique des stocks. Grenoble: A.N.R.T, Université Pierre Mendes France (Grenoble II), 1994.
Find full textAragon, Yves. Séries temporelles avec R. Paris: Springer Paris, 2011. http://dx.doi.org/10.1007/978-2-8178-0208-4.
Full textGourieroux, Christian. Séries temporelles et modèles dynamiques. Paris: Economica, 1990.
Find full textThionbiano, Taladidia. ECONOMÉTRIE DES SÉRIES TEMPORELLES - Cours et exercices. Paris: Editions L'Harmattan, 2008.
Find full textservice), SpringerLink (Online, ed. Séries temporelles avec R: Méthodes et cas. Paris: Springer Paris, 2011.
Find full textBook chapters on the topic "Analyse en séries temporelles"
Aragon, Yves. "Séries temporelles non stationnaires." In Pratique R, 97–120. Paris: Springer Paris, 2011. http://dx.doi.org/10.1007/978-2-8178-0208-4_5.
Full textAragon, Yves. "R pour les séries temporelles." In Pratique R, 21–38. Paris: Springer Paris, 2011. http://dx.doi.org/10.1007/978-2-8178-0208-4_2.
Full textAragon, Yves. "Démarche de base en séries temporelles." In Pratique R, 1–20. Paris: Springer Paris, 2011. http://dx.doi.org/10.1007/978-2-8178-0208-4_1.
Full textAragon, Yves. "Modèles de base en séries temporelles." In Pratique R, 57–95. Paris: Springer Paris, 2011. http://dx.doi.org/10.1007/978-2-8178-0208-4_4.
Full text"Bibliographie." In Analyse des séries temporelles, 345–52. Dunod, 2016. http://dx.doi.org/10.3917/dunod.bourb.2016.01.0345.
Full textDUMITRU, Corneliu Octavian, and Mihai DATCU. "Analyse sémantique de séries chronologiques d’images satellitaires." In Détection de changements et analyse des séries temporelles d’images 2, 99–123. ISTE Group, 2024. http://dx.doi.org/10.51926/iste.9057.ch3.
Full textCONRADSEN, Knut, Henning SKRIVER, Morton J. CANTY, and Allan A. NIELSEN. "Détection de séries de changements dans des séries d’images SAR polarimétriques." In Détection de changements et analyse des séries temporelles d’images 1, 41–81. ISTE Group, 2022. http://dx.doi.org/10.51926/iste.9056.ch2.
Full textMOLINIER, Matthieu, Jukka MIETTINEN, Dino IENCO, Shi QIU, and Zhe ZHU. "Analyse de séries chronologiques d’images satellitaires optiques pour des applications environnementales." In Détection de changements et analyse des séries temporelles d’images 2, 125–74. ISTE Group, 2024. http://dx.doi.org/10.51926/iste.9057.ch4.
Full textATTO, Abdourrahmane M., Fatima KARBOU, Sophie GIFFARD-ROISIN, and Lionel BOMBRUN. "Clustering fonctionnel de séries d’images par entropies relatives." In Détection de changements et analyse des séries temporelles d’images 1, 121–38. ISTE Group, 2022. http://dx.doi.org/10.51926/iste.9056.ch4.
Full textHEDHLI, Ihsen, Gabriele MOSER, Sebastiano B. SERPICO, and Josiane ZERUBIA. "Champs de Markov et séries chronologiques d’images multicapteurs et multirésolution." In Détection de changements et analyse des séries temporelles d’images 2, 5–39. ISTE Group, 2024. http://dx.doi.org/10.51926/iste.9057.ch1.
Full textConference papers on the topic "Analyse en séries temporelles"
AOUDJ, Cherif, Abdelkarim MEZHOUD, Mokhtar GUERFI, and Yacine HAMDENE. "Analyse des variations spatio-temporelles du littoral sableux : Est Béjaoui (Algérie)." In Conférence Méditerranéenne Côtière et Maritime - Coastal and Maritime Mediterranean Conference. Editions Paralia, 2017. http://dx.doi.org/10.5150/cmcm.2017.002.
Full textLAFON, Virginie, Arthur ROBINET, Tatiana DONNAY, David DOXARAN, Bertrand LUBAC, Eric MANEUX, Aldo SOTTOLICHIO, and Olivier HAGOLLE. "RIVERCOLOR : chaîne de traitement des séries temporelles LANDSAT, SPOT et MODIS dédiée à la cartographie des matières en suspension en zone estuarienne." In Journées Nationales Génie Côtier - Génie Civil. Editions Paralia, 2014. http://dx.doi.org/10.5150/jngcgc.2014.067.
Full textVOLTO, Natacha, Virginie DUVAT, Louise BURBAN, and Myriam VENDÉ-LECLERC. "Analyse de l’évolution du trait de côte sur l’atoll d’Ouvéa (Nouvelle-Calédonie) sur 67 ans à partir d'images : quelles dynamiques temporelles?" In Journées Nationales Génie Cotier - Genie Civil, 545–54. Editions Paralia, 2024. http://dx.doi.org/10.5150/jngcgc.2024.057.
Full textReports on the topic "Analyse en séries temporelles"
Perreault, L., A. Nicault, É. Boucher, D. Arseneault, and F. Gennaretti. Analyse des changements de régimes dans les séries temporelles issues de la dendrochronologie. Natural Resources Canada/CMSS/Information Management, 2021. http://dx.doi.org/10.4095/328084.
Full textNicault, A., L. Cournoyer, T. Labarre, and Y. Bégin. Analyse des relations entre le climat et les séries temporelles de densité de cerne. Natural Resources Canada/CMSS/Information Management, 2021. http://dx.doi.org/10.4095/328074.
Full textDufour, Quentin, David Pontille, and Didier Torny. Contracter à l’heure de la publication en accès ouvert. Une analyse systématique des accords transformants. Ministère de l'enseignement supérieur et de la recherche, April 2021. http://dx.doi.org/10.52949/2.
Full textMegersa, Kelbesa. Technologie et fiscalité : Adoption et impact des services électroniques au Rwanda. Institute of Development Studies, May 2024. http://dx.doi.org/10.19088/ictd.2024.069.
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