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Box–Cox symmetric distributions and applications to nutritional data

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  • Silvia L. P. Ferrari

    (University of São Paulo)

  • Giovana Fumes

    (University of São Paulo)

Abstract

We introduce and study the Box–Cox symmetric class of distributions, which is useful for modeling positively skewed, possibly heavy-tailed, data. The new class of distributions includes the Box–Cox t, Box–Cox Cole-Green (or Box–Cox normal), Box–Cox power exponential distributions, and the class of the log-symmetric distributions as special cases. It provides easy parameter interpretation, which makes it convenient for regression modeling purposes. Additionally, it provides enough flexibility to handle outliers. The usefulness of the Box–Cox symmetric models is illustrated in a series of applications to nutritional data.

Suggested Citation

  • Silvia L. P. Ferrari & Giovana Fumes, 2017. "Box–Cox symmetric distributions and applications to nutritional data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 101(3), pages 321-344, July.
    • Handle: RePEc:spr:alstar:v:101:y:2017:i:3:d:10.1007_s10182-017-0291-6
    DOI: 10.1007/s10182-017-0291-6
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    References listed on IDEAS

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    Cited by:

    1. Giovana Fumes-Ghantous & Silvia L. P. Ferrari & José Eduardo Corrente, 2018. "Box–Cox t random intercept model for estimating usual nutrient intake distributions," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(4), pages 715-734, December.

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