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Distribution of the inter and intra inertia in conditional MCA

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Abstract

Conditional Multiple Correspondence Analysis (MCA), where a control variable plays the role of a partition model, allows us to decompose global inertia into between inertia and within inertia. The problem is to assess when the conditioning variable gives different results with respect to the unconditional analysis. In this paper, we study the asymptotic distribution function of these inertias, which can allow us to determine whether conditioning is significant. Some simulations were performed to corroborate the established results.

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Authors and Affiliations

  1. Dept. of Computer Science and Applied Mathematics, Univ.de Girona., Av. Lluís Santaló s/n, 17071, Girona, Spain

    Josep Daunis-i-Estadella & Santiago Thió-Henestrosa

  2. Dept. of Statistics and Operations Research, Univ. Politècnica de Catalunya, Pau Gargallo, 5 08028, Barcelona, Spain

    Tomàs Aluja-Banet

Authors
  1. Josep Daunis-i-Estadella
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  2. Tomàs Aluja-Banet
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  3. Santiago Thió-Henestrosa
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Daunis-i-Estadella, J., Aluja-Banet, T. & Thió-Henestrosa, S. Distribution of the inter and intra inertia in conditional MCA. Computational Statistics 20, 449–463 (2005). https://doi.org/10.1007/BF02741308

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