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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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Time series analysis of injuries
Statistics in Medicine, 1989AbstractWe used time series models in the exploratory and confirmatory analysis of selected fatal injuries in the United States from 1972 to 1983. We built autoregressive integrated moving average (ARIMA) models for monthly, weekly, and daily series of deaths and used these models to generate hypotheses.
B, Martinez-Schnell, A, Zaidi
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Permutations and time series analysis
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2009The main aim of this paper is to show how the use of permutations can be useful in the study of time series analysis. In particular, we introduce a test for checking the independence of a time series which is based on the number of admissible permutations on it.
Cánovas, Jose S., Guillamón, Antonio
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Interactive analysis of time series
Proceedings of seventh international conference on APL - APL '75, 1975A great deal of data in business, economics, engineering and the natural sciences occur in the form of time series where observations are dependent and where the nature of this dependence is of interest in itself. The technics used in the analysis of such series of dependent observations is called time series analysis.The purpose is to build stochastic
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OUTLIER DIAGNOSTICS IN TIME SERIES ANALYSIS
Journal of Time Series Analysis, 1990Abstract.Cook's likelihood displacement is a convenient measure of the impact of a model perturbation on parameter estimates. A commonly used model perturbation in regression is the deletion of acase, or equation. A natural model perturbation in the time series context is the deletion of anobservation, or a group of observations.
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Some remarks on the analysis of time-series
Biometrika, 1967Techniques involving the direct study of the spectrum when analyzing time-series are reviewed, and comments made on such topics as estimating the spectral density function, testing for mixed spectra, eliminating a trend, cross-spectral analysis, and non-normality.
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A Review on Outlier/Anomaly Detection in Time Series Data
ACM Computing Surveys, 2022U Mori +2 more
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