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Wavelets in time-series analysis
Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences, 1999Abstract Reviewing the role of wavelets in statistical time-series analysis (TSA) appears to be quite an impossible task. For one thing, wavelets have become so popular that such a review could never be exhaustive. Another, more pertinent, reason is that there is no such thing as one statistical time-series analysis, as the very many ...
Nason, GP, von Sachs, R
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Diagnostics for Time Series Analysis
Journal of Time Series Analysis, 1999Test statistics are proposed to determine the goodness of fit of a time series model. The test statistics are based on a sequence of random variables that are independent and standard normal if the model is correct. The paper shows how to compute this sequence of random variables efficiently using a combination of Markov chain Monte Carlo and ...
Gerlach, Richard +2 more
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nonlinear time series analysis [PDF]
, 2008 Since the early 1980s, there has been a growing interest in stochastic nonlinear dynamical systems of the form, where is a zero mean, covariance stationary process, is the conditional volatility, and is an independent and identically distributed noise process.
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Time series reconstruction analysis
2016 IEEE 8th International Conference on Intelligent Systems (IS), 2016The dimensionality of time series data is usually very large, so it must often be reduced before applying certain data mining tasks upon it. Dimensionality reduction is achieved by creating appropriate time series representation that is actually new time series of lower dimensionality obtained from the original one by preserving only the important ...
Kurbalija, Vladimir, Bratić, Brankica
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A Framework for Time-Series Analysis
2010The popularity of time-series databases in many applications has created an increasing demand for performing data-mining tasks (classification, clustering, outlier detection, etc.) on time-series data. Currently, however, no single system or library exists that specializes on providing efficient implementations of data-mining techniques for time-series
Vladimir Kurbalija +3 more
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Acycle: Time-series analysis software for paleoclimate research and education
Computational Geosciences, 2019Recognition and interpretation of paleoclimate signals in sedimentary proxy datasets are time consuming and subjective. Acycle is a comprehensive and easy-to-use software package for time series analysis in paleoclimate research and education.
Mingsong Li, L. Hinnov, L. Kump
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Causal inference for time series analysis: problems, methods and evaluation
Knowledge and Information Systems, 2021Time series data are a collection of chronological observations which are generated by several domains such as medical and financial fields. Over the years, different tasks such as classification, forecasting and clustering have been proposed to analyze ...
Raha Moraffah +7 more
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2018
Analysis of epidemic time series is a large endeavor because of the richness of dynamical patterns and plentitude of historical data (Rohani and King 2010). A wide range of tools are used, some of which are borrowed from mainstream statistics other of which are “custom made.” The classic “mainstream” methods belong to two categories: the so-called time-
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Analysis of epidemic time series is a large endeavor because of the richness of dynamical patterns and plentitude of historical data (Rohani and King 2010). A wide range of tools are used, some of which are borrowed from mainstream statistics other of which are “custom made.” The classic “mainstream” methods belong to two categories: the so-called time-
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ANALYSIS OF TIME SERIES WITH WAVELETS
International Journal of Wavelets, Multiresolution and Information Processing, 2007A financial time series analysis method based on the theory of wavelets is proposed. It is based on the transformation of data of the series in the corresponding wavelet coefficients and in the analysis of the latter, which represent the local characteristics of the series better. In particular, an algorithm for short term previsions is defined.
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Multi-modal Time Series Analysis: A Tutorial and Survey
Knowledge Discovery and Data MiningMulti-modal time series analysis has recently emerged as a prominent research area, driven by the increasing availability of diverse data modalities, such as text, images, and structured tabular data from real-world sources.
Yushan Jiang +9 more
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