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Joint regression modeling of location and scale parameters of the skew t distribution with application in soil chemistry data

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  • F. Prataviera
  • A. M. Batista
  • P. L. Libardi
  • G. M. Cordeiro
  • E. M. M. Ortega

Abstract

In regression model applications, the errors may frequently present a symmetric shape. In such cases, the normal and Student t distributions are commonly used. In this paper, we shall be concerned only to model heavy-tailed, skewed errors and absence of variance homogeneity with two regression structures based on the skew t distribution. We consider a classic analysis for the parameters of the proposed model. We perform a diagnostic analysis based on global influence and quantile residuals. For different parameter settings and sample sizes, various simulation results are obtained and compared to evaluate the performance of the skew t regression. Further, we illustrate the usefulness of the new regression by means of a real data set (amount of potassium in different soil areas) from a study carried out at the Department of Soil Science of the Luiz de Queiroz School of Agriculture, University of São Paulo.

Suggested Citation

  • F. Prataviera & A. M. Batista & P. L. Libardi & G. M. Cordeiro & E. M. M. Ortega, 2022. "Joint regression modeling of location and scale parameters of the skew t distribution with application in soil chemistry data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 49(1), pages 195-213, January.
    • Handle: RePEc:taf:japsta:v:49:y:2022:i:1:p:195-213
    DOI: 10.1080/02664763.2020.1801608
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