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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-
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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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TIME SERIES ANALYSIS IN DREAM RESEARCH
Perceptual and Motor Skills, 2000The present study investigated the linear as well as nonlinear relationships between selected dream content scales and dream length. The results indicated that biases due to control solely for the linear components are almost negligible.
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