Many time series are of short duration because data acquisition has, of necessity, proceeded for but a brief term. Such data have previously often been analyzed by methods that either do not explicitly take into account time related changes or that are designed for long time series. In this paper, we consider several ways of assigning a dissimilarity between univariate time series in short term behavior. In particular, we have defined a measure that works irrespective of different baselines and scaling factors and its effectiveness has been evaluated on real and synthetic data sets.

Classification of short time series / Tarsitano, Agostino. - In: ADVANCES AND APPLICATIONS IN STATISTICAL SCIENCES. - ISSN 0974-6811. - 1(2010), pp. 215-231.

Classification of short time series

TARSITANO, Agostino
2010

Abstract

Many time series are of short duration because data acquisition has, of necessity, proceeded for but a brief term. Such data have previously often been analyzed by methods that either do not explicitly take into account time related changes or that are designed for long time series. In this paper, we consider several ways of assigning a dissimilarity between univariate time series in short term behavior. In particular, we have defined a measure that works irrespective of different baselines and scaling factors and its effectiveness has been evaluated on real and synthetic data sets.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/122785
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