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Independent Component Analysis for Extended Time Series in Climate Data

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Book cover Advances in Regression, Survival Analysis, Extreme Values, Markov Processes and Other Statistical Applications

Part of the book series: Studies in Theoretical and Applied Statistics ((STASSPSS))

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Abstract

Various techniques of multivariate data analysis have been proposed to study time series, including the multi-channel singular spectrum analysis (MSSA). This technique is a principal component analysis (PCA) of the extended matrix of initial lagged series, also called extended empirical orthogonal function (EEOF) analysis in a climatological context. This work uses independent component analysis (ICA) as an alternative to the MSSA method, when studying the extended time series matrix. Often, ICA is more appropriate than PCA to analyse time series, since the extraction of independent components (ICs) involves higher-order statistics whereas PCA only uses the second-order statistics to obtain the principal components (PCs), which are not correlated and are not necessarily independent. An example of time series for meteorological data and some comparative results between the techniques under study are given. Different methods of ordering ICs are also presented, including a new one, which may influence the quality of the reconstruction of the original data.

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Acknowledgements

The authors would like to thank CM-UTAD and to the research funded by the Portuguese Government through the FCT (Fundação para a Ciência e Tecnologia) under the project PEst-OE/MAT/UI4080/2011 for the financial support for this study.

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Authors and Affiliations

  1. Department of Mathematics, School of Technology and Management, Polytechnic Institute of Leiria, and CM-UTAD, Campus 2, Morro do Lena - Alto do Vieiro, Apartado 4163, 2411-901, Leiria, Portugal

    Fernando Sebastião

  2. Department of Mathematics, University of Trás-os-Montes and Alto Douro, and CM-UTAD, Apartado 1013, 5001-801, Vila Real, Portugal

    Irene Oliveira

Authors
  1. Fernando Sebastião
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  2. Irene Oliveira
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Corresponding author

Correspondence to Fernando Sebastião .

Editor information

Editors and Affiliations

  1. , Universidade Nova de Lisboa, CMA and Faculdade de Ciˆenciase Tecnolog, Caparica, Caparica, 2829-516, Portugal

    João Lita da Silva

  2. , Universidade Nova de Lisboa, CMA and Faculdade de Ciˆenciase Tecnolog, Caparica, Caparica, 2829-516, Portugal

    Frederico Caeiro

  3. , Universidade Nova de Lisboa, CEAUL and Faculdade de Ciˆenciase Tecnol, Caparica, Caparica, 2829-516, Portugal

    Isabel Natário

  4. , Universidade Nova de Lisboa,, CEAUL and Faculdade de Ciˆenciase Tecnol, Caparica 59, Caparica, 2829-516, Portugal

    Carlos A. Braumann

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Sebastião, F., Oliveira, I. (2013). Independent Component Analysis for Extended Time Series in Climate Data. In: Lita da Silva, J., Caeiro, F., Natário, I., Braumann, C. (eds) Advances in Regression, Survival Analysis, Extreme Values, Markov Processes and Other Statistical Applications. Studies in Theoretical and Applied Statistics(). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34904-1_45

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