Relevant bibliographies by topics / Long-memory processes

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Long-memory processes'

Author: Grafiati
Published: 4 June 2021
Last updated: 27 April 2022

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Journal articles on the topic "Long-memory processes"

1

Ray, W. D., and J. Beran. "Statistics for Long-Memory Processes." Journal of the Royal Statistical Society. Series A (Statistics in Society) 159, no. 1 (1996): 180. http://dx.doi.org/10.2307/2983481.

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Percival, Donald B., and Jan Beran. "Statistics for Long-Memory Processes." Journal of the American Statistical Association 91, no. 435 (1996): 1378. http://dx.doi.org/10.2307/2291761.

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Glosup, Jeffrey. "Statistics for Long-Memory Processes." Technometrics 39, no. 1 (1997): 105–6. http://dx.doi.org/10.1080/00401706.1997.10485452.

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Ding, Yiming, Yaozhong Hu, Weilin Xiao, and Litan Yan. "Long-Memory Processes and Applications." Abstract and Applied Analysis 2014 (2014): 1–2. http://dx.doi.org/10.1155/2014/384085.

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Biao Wu, Wei. "Empirical processes of long-memory sequences." Bernoulli 9, no. 5 (2003): 809–31. http://dx.doi.org/10.3150/bj/1066418879.

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Samorodnitsky, Gennady. "Long memory and self-similar processes." Annales de la faculté des sciences de Toulouse Mathématiques 15, no. 1 (2006): 107–23. http://dx.doi.org/10.5802/afst.1115.

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Bisognin, C., and S. R. C. Lopes. "Properties of seasonal long memory processes." Mathematical and Computer Modelling 49, no. 9-10 (2009): 1837–51. http://dx.doi.org/10.1016/j.mcm.2008.12.003.

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Wu, Wei Biao, Yinxiao Huang, and Wei Zheng. "Covariances Estimation for Long-Memory Processes." Advances in Applied Probability 42, no. 01 (2010): 137–57. http://dx.doi.org/10.1017/s0001867800003943.

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For a time series, a plot of sample covariances is a popular way to assess its dependence properties. In this paper we give a systematic characterization of the asymptotic behavior of sample covariances of long-memory linear processes. Central and noncentral limit theorems are obtained for sample covariances with bounded as well as unbounded lags. It is shown that the limiting distribution depends in a very interesting way on the strength of dependence, the heavy-tailedness of the innovations, and the magnitude of the lags.
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Wu, Wei Biao, Yinxiao Huang, and Wei Zheng. "Covariances Estimation for Long-Memory Processes." Advances in Applied Probability 42, no. 1 (2010): 137–57. http://dx.doi.org/10.1239/aap/1269611147.

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For a time series, a plot of sample covariances is a popular way to assess its dependence properties. In this paper we give a systematic characterization of the asymptotic behavior of sample covariances of long-memory linear processes. Central and noncentral limit theorems are obtained for sample covariances with bounded as well as unbounded lags. It is shown that the limiting distribution depends in a very interesting way on the strength of dependence, the heavy-tailedness of the innovations, and the magnitude of the lags.
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Lee, Kyeongmin, and Changryong Baek. "Outlier detection for long memory processes." Journal of the Korean Data And Information Science Society 32, no. 6 (2021): 1205–18. http://dx.doi.org/10.7465/jkdi.2021.32.6.1205.

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Dissertations / Theses on the topic "Long-memory processes"

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Neto, Fernando Fernandes. "Essays on long memory processes." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/3/3139/tde-03032017-104452/.

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The present work aims at discussing the main theoretical aspects related to the occurrence of long memory processes and its respective application in economics and finance. In order to discuss the main theoretical aspects of its occurrence, it is worth starting from the complex systems approach and emergent phenomena, keeping in mind that many of these are computationally irreducible. In other words, the current state of the system depends on all previous states, in such a way that any change in the initial configuration must cause a significant difference in all posterior states. That is, the
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Golinski, Adam. "Asset pricing with long memory processes." Thesis, Imperial College London, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.534973.

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Hwang, Soosung. "Essays on long memory processes and volatility." Thesis, University of Cambridge, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.286421.

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Craigmile, Peter Francis. "Wavelet-based estimation for trend contaminated long memory processes /." Thesis, Connect to this title online; UW restricted, 2000. http://hdl.handle.net/1773/8967.

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Zhu, Beijia. "Analysis of non-stationary (seasonal/cyclical) long memory processes." Thesis, Paris 1, 2013. http://www.theses.fr/2013PA010013/document.

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La mémoire longue, aussi appelée la dépendance à long terme (LRD), est couramment détectée dans l’analyse de séries chronologiques dans de nombreux domaines, par exemple,en finance, en économétrie, en hydrologie, etc. Donc l’étude des séries temporelles à mémoire longue est d’une grande valeur. L’introduction du processus ARFIMA (fractionally autoregressive integrated moving average) établit une relation entre l’intégration fractionnaire et la mémoire longue, et ce modèle a trouvé son pouvoir de prévision à long terme, d’où il est devenu l’un des modèles à mémoire longue plus populaires dans l
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Mudelsee, Manfred. "Long memory and the aggregation of AR(1) processes." Universität Leipzig, 2006. https://ul.qucosa.de/id/qucosa%3A15498.

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Granger (1980) found that the aggregation of m short-memory AR(1) processes yields a long-memory process. Thereby he assumed m -> ∞, Gaussian shape and betadistributed AR(1) parameters over (0; 1). To test hypotheses that long memory in climate time series comes from aggregation, the finding of Granger (1980) cannot be directly applied. First, the number of \'microclimatic\' processes to be aggregated is finite. Second, climatic processes often produce right-skewed data. Third, the AR(1) parameters of the microclimatic processes could be restricted to a narrower interval than (0; 1). We theref
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Mudelsee, Manfred. "Long memory and the aggregation of AR(1) processes." Universitätsbibliothek Leipzig, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-222017.

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Granger (1980) found that the aggregation of m short-memory AR(1) processes yields a long-memory process. Thereby he assumed m -> ∞, Gaussian shape and betadistributed AR(1) parameters over (0; 1). To test hypotheses that long memory in climate time series comes from aggregation, the finding of Granger (1980) cannot be directly applied. First, the number of \"microclimatic\" processes to be aggregated is finite. Second, climatic processes often produce right-skewed data. Third, the AR(1) parameters of the microclimatic processes could be restricted to a narrower interval than (0; 1). We the
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Graves, Timothy. "A systematic approach to Bayesian inference for long memory processes." Thesis, University of Cambridge, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.608183.

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Marklund, Petter. "Shared component processes in working memory and long-term memory : Insights from functional brain imaging." Licentiate thesis, Umeå University, Department of Psychology, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-14731.

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<p>Marklund, P. (2004). Shared component processes in working memory and long-term memory: Insights from functional brain imaging. Department of Psychology, Umeå University, S-901 87 Umeå SwedenRecent findings from functional neuroimaging studies have shown pronounced similarities in the functional brain activity patterns associated with tests of various cognitive functions. This thesis investigates shared component processes in working memory and declarative long-term memory. Study 1 showed a common pattern of increased activity in four anatomically distinct regions in prefrontal cortex durin
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Shumeyko, Yevgen [Verfasser]. "Data adaptive wavelet methods for Gaussian long-memory processes / Yevgen Shumeyko." Konstanz : Bibliothek der Universität Konstanz, 2012. http://d-nb.info/1023210363/34.

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Books on the topic "Long-memory processes"

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Beran, Jan, Yuanhua Feng, Sucharita Ghosh, and Rafal Kulik. Long-Memory Processes. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35512-7.

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Statistics for long-memory processes. Chapman & Hall, 1994.

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Silvapulle, Paramsothy. Testing stationary nonnested short memory against long memory processes. La Trobe University, Schools of Economics and Commerce, 1996.

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Tschernig, Rolf. Wechselkurse, Unsicherheit und Long Memory. Physica-Verlag, 1994.

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Smith, Albert F. Cognitive processes in long-term dietary recall. U.S. Dept. of Health and Human Services, Public Health Service, Centers for Disease Control, National Center for Health Statistics, 1991.

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Restak, Richard M. Older and wiser: How to maintain peak mental ability for as long as you live. Thorndike Press, 1998.

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Older and wiser: How to maintain peak mental ability for as long as you live. Simon & Schuster, 1997.

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Long memory processes in speculative markets. 1993.

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Large Sample Inference For Long Memory Processes. Imperial College Press, 2011.

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Giraitis, Liudas, Hira L. Koul, and Donatas Surgailis. Large Sample Inference for Long Memory Processes. IMPERIAL COLLEGE PRESS, 2012. http://dx.doi.org/10.1142/p591.

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Book chapters on the topic "Long-memory processes"

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Cowpertwait, Paul S. P., and Andrew V. Metcalfe. "Long-Memory Processes." In Introductory Time Series with R. Springer New York, 2009. http://dx.doi.org/10.1007/978-0-387-88698-5_8.

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Kulik, Rafał, and Philippe Soulier. "Long memory processes." In Heavy-Tailed Time Series. Springer New York, 2020. http://dx.doi.org/10.1007/978-1-0716-0737-4_16.

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Beran, Jan, Yuanhua Feng, Sucharita Ghosh, and Rafal Kulik. "Definition of Long Memory." In Long-Memory Processes. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35512-7_1.

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Beran, Jan, Yuanhua Feng, Sucharita Ghosh, and Rafal Kulik. "Resampling." In Long-Memory Processes. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35512-7_10.

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Beran, Jan, Yuanhua Feng, Sucharita Ghosh, and Rafal Kulik. "Origins and Generation of Long Memory." In Long-Memory Processes. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35512-7_2.

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Beran, Jan, Yuanhua Feng, Sucharita Ghosh, and Rafal Kulik. "Mathematical Concepts." In Long-Memory Processes. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35512-7_3.

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Beran, Jan, Yuanhua Feng, Sucharita Ghosh, and Rafal Kulik. "Limit Theorems." In Long-Memory Processes. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35512-7_4.

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Beran, Jan, Yuanhua Feng, Sucharita Ghosh, and Rafal Kulik. "Statistical Inference for Stationary Processes." In Long-Memory Processes. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35512-7_5.

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Beran, Jan, Yuanhua Feng, Sucharita Ghosh, and Rafal Kulik. "Statistical Inference for Nonlinear Processes." In Long-Memory Processes. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35512-7_6.

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Beran, Jan, Yuanhua Feng, Sucharita Ghosh, and Rafal Kulik. "Statistical Inference for Nonstationary Processes." In Long-Memory Processes. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35512-7_7.

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Conference papers on the topic "Long-memory processes"

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"Momentum Strategies for Long-Memory Processes." In 2005 European Real Estate Society conference in association with the International Real Estate Society: ERES Conference 2005. ERES, 2005. http://dx.doi.org/10.15396/eres2005_225.

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GRANGER, CLIVE W. J. "LONG MEMORY PROCESSES - AN ECONOMIST'S VIEWPOINT." In Proceedings of the Wollongong Conference. WORLD SCIENTIFIC, 2002. http://dx.doi.org/10.1142/9789812776372_0011.

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Wendt, H., A. Scherrer, P. Abry, and S. Achard. "Testing fractal connectivity in multivariate long memory processes." In ICASSP 2009 - 2009 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2009. http://dx.doi.org/10.1109/icassp.2009.4960233.

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"The empirical properties of some popular estimators of long memory processes." In 19th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand (MSSANZ), Inc., 2011. http://dx.doi.org/10.36334/modsim.2011.d3.rea.

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Arefaine, Fanus, Meng Duan, Ravi Tiwari, et al. "Using Long Short-Term Memory (LSTM) Network to Predict Negative-Bias Temperature Instability." In 2021 International Conference on Simulation of Semiconductor Processes and Devices (SISPAD). IEEE, 2021. http://dx.doi.org/10.1109/sispad54002.2021.9592531.

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Lin-Wen Cheng and Song-Wei Wang. "Determining long memory processes parameters based on multi-scale maximum likelihood estimation." In Proceedings of 2005 International Conference on Machine Learning and Cybernetics. IEEE, 2005. http://dx.doi.org/10.1109/icmlc.2005.1527859.

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Wang, Kai, Junghui Chen, and Zhihuan Song. "Quality-relevant Dynamic Modelling and Phase Division with Long Short-term Memory for Batch Processes." In 2018 Chinese Automation Congress (CAC). IEEE, 2018. http://dx.doi.org/10.1109/cac.2018.8623463.

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Liu, Fan, Peiliang Wang, Zhiduan Cai, Zhe Zhou, Yanfeng Wang, and Zeyu Yang. "Batch Process Fault Diagnosis Based on The Combination of Deep Belief Network and Long Short-Term Memory Network." In 2019 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS). IEEE, 2019. http://dx.doi.org/10.1109/safeprocess45799.2019.9213407.

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Gurau, Carmela. "THE LONG TERM CORROSION BEHAVIOR OF A SHAPE MEMORY ALLOY IN SEAWATER SUBJECTED TO VARIOUS PLASTIC DEFORMATION PROCESSES." In 14th SGEM GeoConference on NANO, BIO AND GREEN � TECHNOLOGIES FOR A SUSTAINABLE FUTURE. Stef92 Technology, 2014. http://dx.doi.org/10.5593/sgem2014/b61/s24.024.

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Hallihan, Gregory M., and L. H. Shu. "Creativity and Long-Term Potentiation: Implications for Design." In ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/detc2011-48595.

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An emerging research trend has seen concepts from cognitive psychology applied to enhance the creative design process through a more detailed understanding of the underlying cognitive mechanisms. However, the physiological processes by which the human element achieves creative solutions have only recently received significant attention. Understanding the mechanisms that allow the brain to change in response to experience may have implications for creative thought processes. Long-term potentiation (LTP) is one such mechanism, and has already been implicated in learning and memory development. T
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Reports on the topic "Long-memory processes"

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Yahav, Shlomo, John Brake, and Noam Meiri. Development of Strategic Pre-Natal Cycling Thermal Treatments to Improve Livability and Productivity of Heavy Broilers. United States Department of Agriculture, 2013. http://dx.doi.org/10.32747/2013.7593395.bard.

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The necessity to improve broiler thermotolerance and live performance led to the following hypothesis: Appropriate comprehensive incubation treatments that include significant temperature management changes will promote angiogenesis and will improve acquisition of thermotolerance and carcass quality of heavy broilers through epigenetic adaptation. It was based on the following questions: 1. Can TM during embryogenesis of broilers induce a longer-lasting thermoregulatory memory (up to marketing age of 10 wk) that will improve acquisition of thermotolerance as well as increased breast meat yield
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