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Biplots in Covariance Analysis

Author

Listed:
  • Opeoluwa FO

    (Department of Statistics and Population Studies, University of Namibia, South Africa)

  • Sugnet L

    (Department of Statistics and Actuarial Science, Stellenbosch University, South Africa)

Abstract

Among the various statistical techniques useful for exploring the relationships between different sets of variables is the Covariance Analysis. Since biplots in general are useful graphical tools for exploring the relationships between (multivariate) variables, the biplot is employed in the covariance analysis framework to form the covariance biplot. The resulting biplot provides a single graphical display of the variables and inter-variables relationships. An illustration is shown using a mineral sorting production data consisting of five hundred and seventy-two processes.

Suggested Citation

  • Opeoluwa FO & Sugnet L, 2017. "Biplots in Covariance Analysis," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 3(5), pages 147-154, November.
    • Handle: RePEc:adp:jbboaj:v:3:y:2017:i:5:p:147-154
    DOI: 10.19080/BBOAJ.2017.03.555623
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    References listed on IDEAS

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    2. Opeoluwa F. Oyedele & Sugnet Lubbe, 2015. "The construction of a partial least-squares biplot," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(11), pages 2449-2460, November.
    3. Ulrich Kohler & Magdalena Luniak, 2005. "Data inspection using biplots," Stata Journal, StataCorp LP, vol. 5(2), pages 208-233, June.
    4. Mevik, Björn-Helge & Wehrens, Ron, 2007. "The pls Package: Principal Component and Partial Least Squares Regression in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 18(i02).
    Full references (including those not matched with items on IDEAS)

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