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Descriptive measures of multivariate scatter and linear dependence

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  • Peña, Daniel
  • Rodríguez, Julio

Abstract

In this paper we propose two new descriptive measures for multivariate data: the effective variance and the effective dependence. These measures have a direct geometric and statistical interpretation and can be used to compare groups with different number of variables. The contribution of these measures to understanding multivariate data is illustrated by several examples.

Suggested Citation

  • Peña, Daniel & Rodríguez, Julio, 2003. "Descriptive measures of multivariate scatter and linear dependence," Journal of Multivariate Analysis, Elsevier, vol. 85(2), pages 361-374, May.
    • Handle: RePEc:eee:jmvana:v:85:y:2003:i:2:p:361-374
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    References listed on IDEAS

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    1. Mustonen, Seppo, 1997. "A measure for total variability in multivariate normal distribution," Computational Statistics & Data Analysis, Elsevier, vol. 23(3), pages 321-334, January.
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    Cited by:

    1. Luis J. Álvarez & Maria Dolores Gadea & Ana Gómez‐Loscos, 2021. "Inflation comovements in advanced economies: Facts and drivers," The World Economy, Wiley Blackwell, vol. 44(2), pages 485-509, February.
    2. Jorge Gonzalez-Chapela, 2005. "On Measuring Convergence in the Use of Time," MEA discussion paper series 05096, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    3. Dariush Najarzadeh, 2019. "Testing equality of standardized generalized variances of k multivariate normal populations with arbitrary dimensions," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(4), pages 593-623, December.
    4. Iliopoulos, George, 2008. "UMVU estimation of the ratio of powers of normal generalized variances under correlation," Journal of Multivariate Analysis, Elsevier, vol. 99(6), pages 1051-1069, July.
    5. Luis J. Álvarez & Ana Gómez-Loscos & María Dolores Gadea, 2019. "Inflation interdependence in advanced economies," Working Papers 1920, Banco de España.
    6. Giuliodori, Andrea, 2009. "Clustering and classifying images with local and global variability," DES - Working Papers. Statistics and Econometrics. WS ws090101, Universidad Carlos III de Madrid. Departamento de Estadística.

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