Estimating growth charts via nonparametric quantile regression: a practical framework with application in ecology

Environmental and Ecological Statistics volume 20, pages519–531(2013)Cite this article

Abstract

We discuss a practical and effective framework to estimate reference growth charts via regression quantiles. Inequality constraints are used to ensure both monotonicity and non-crossing of the estimated quantile curves and penalized splines are employed to model the nonlinear growth patterns with respect to age. A companion R package is presented and relevant code discussed to favour spreading and application of the proposed methods.

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Acknowledgments

The authors would like to thank the referee for his/her valuable comments.

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Affiliations

  1. Dipartimento Scienze Statistiche e Matematiche ‘Vianelli’, Università di Palermo, Palermo, Italy

    Vito M. R. Muggeo & Mariangela Sciandra

  2. Dipartimento Scienze della Terra e del Mare, Università di Palermo, Palermo, Italy

    Agostino Tomasello & Sebastiano Calvo

Authors
  1. Vito M. R. Muggeo
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  2. Mariangela Sciandra
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  3. Agostino Tomasello
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  4. Sebastiano Calvo
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Corresponding author

Correspondence to Vito M. R. Muggeo.

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Handling Editor: Ashis SenGupta.

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Muggeo, V.M.R., Sciandra, M., Tomasello, A. et al. Estimating growth charts via nonparametric quantile regression: a practical framework with application in ecology. Environ Ecol Stat 20, 519–531 (2013). https://doi.org/10.1007/s10651-012-0232-1

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Keywords

  • Growth charts
  • Nonparametric regression quantiles
  • Penalized splines
  • P. oceanica modelling
  • R software