Abstract
Correspondence analysis (CA) is a method designed to give a graphical representation of a contingency table N and thus to interpret the association between rows and columns. To be specific, correspondence analysis visualises the so-called correspondence matrix P, which is the discrete bivariate density obtained by dividing N by its grand total n: P = (1/n)N. A continuous extension of CA can be obtained by replacing P with a bivariate probability density h(x, y). The marginal densities f(x), g(y) are the continuous counterparts of the row and column margins of P.
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Cuadras, C.M., Fortiana, J., Greenacre, M.J. (2000). Continuous Extensions of Matrix Formulations in Correspondence Analysis, with Applications to the FGM Family of Distributions. In: Heijmans, R.D.H., Pollock, D.S.G., Satorra, A. (eds) Innovations in Multivariate Statistical Analysis. Advanced Studies in Theoretical and Applied Econometrics, vol 36. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-4603-0_7
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