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SSRN Electronic Journal, 2006 Any series of observations ordered along a single dimension, such as time, may be thought of as a time series. The emphasis in time series analysis is on studying the dependence among observations at different points in time. What distinguishes time series analysis from general multivariate analysis is precisely the temporal order imposed on the ...
Francis X. Diebold +2 more
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American Journal of Orthodontics and Dentofacial Orthopedics, 2022
This article describes a simple method of applying a time series analysis to sample data sets using a free and open statistical software program, Language R.Records of new patients who visited 2 different university-affiliated orthodontic departments in 2 different countries were collected.
Richard E. Donatelli +3 more
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This article describes a simple method of applying a time series analysis to sample data sets using a free and open statistical software program, Language R.Records of new patients who visited 2 different university-affiliated orthodontic departments in 2 different countries were collected.
Richard E. Donatelli +3 more
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Foundations of Time Series Analysis
2021For almost a century, classical statistical methods including exponential smoothing and autoregression integrated moving averages (ARIMA) have been predominant in the analysis of time series (TS) and in the pursuit of forecasting future events from historical data.
Jonas, Ort +5 more
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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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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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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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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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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-
openaire +1 more source