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An overview of statistical decomposition techniques applied to complex systems

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  • Tuncer, Yalcin
  • Tanik, Murat M.
  • Allison, David B.

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  • Tuncer, Yalcin & Tanik, Murat M. & Allison, David B., 2008. "An overview of statistical decomposition techniques applied to complex systems," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2292-2310, January.
    • Handle: RePEc:eee:csdana:v:52:y:2008:i:5:p:2292-2310
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    References listed on IDEAS

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    1. Carl Eckart & Gale Young, 1936. "The approximation of one matrix by another of lower rank," Psychometrika, Springer;The Psychometric Society, vol. 1(3), pages 211-218, September.
    2. Li, Baibing & Martin, Elaine B. & Morris, A. Julian, 2002. "On principal component analysis in L1," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 471-474, September.
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    Cited by:

    1. Beaton, Derek & Chin Fatt, Cherise R. & Abdi, Hervé, 2014. "An ExPosition of multivariate analysis with the singular value decomposition in R," Computational Statistics & Data Analysis, Elsevier, vol. 72(C), pages 176-189.
    2. Hon Loong Lam & Jia Chun Ang & Yi Peng Heng & Ho Yan Lee & Adrian Chun Minh Loy & Bing Shen How, 2023. "Synthesis of Biomass Corridor in Peninsular Malaysia via Hybrid Mathematical and Graphical Framework," Sustainability, MDPI, vol. 15(14), pages 1-30, July.
    3. Syed, Fahad Iqbal & Muther, Temoor & Dahaghi, Amirmasoud Kalantari & Negahban, Shahin, 2022. "Low-Rank Tensors Applications for Dimensionality Reduction of Complex Hydrocarbon Reservoirs," Energy, Elsevier, vol. 244(PA).
    4. Colubi, Ana & González-Rodri­guez, Gil & Domi­nguez-Cuesta, Mari­a José & Jiménez-Sánchez, Montserrat, 2008. "Favorability functions based on kernel density estimation for logistic models: A case study," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4533-4543, May.

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