Abstract
Biplots form a useful tool for the graphical exploration of multivariate data sets. A wide variety of biplots has been described for quantitative data sets, contingency tables, correlation matrices and matrices of regression coefficients. These are produced by principal component analysis (PCA), correspondence analysis (CA), canonical correlation analysis (CCO) and redundancy analysis (RDA). The information content of a biplot can be increased by adding scales with tick marks to the biplot arrows, a process called calibration. We describe a general procedure for obtaining scales that is based on finding an optimal calibration factor by generalized least squares. This procedure allows automatic calibration of axes in all forementioned biplots. Use of the optimal calibration factor produces graduations that are identical to Gower’s predictive scales. A procedure for automatically shifting calibrated axes towards the margins of the plot is presented.
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© 2011 Springer-Verlag Berlin Heidelberg
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Graffelman, J. (2011). A Universal Procedure for Biplot Calibration. In: Ingrassia, S., Rocci, R., Vichi, M. (eds) New Perspectives in Statistical Modeling and Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11363-5_22
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DOI: https://doi.org/10.1007/978-3-642-11363-5_22
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