The sinh-normal/independent nonlinear regression model

Filidor Vilca, Camila Borelli Zeller and Gauss M. Cordeiro

Journal of Applied Statistics, 2015, vol. 42, issue 8, 1659-1676

Abstract: The normal/independent family of distributions is an attractive class of symmetric heavy-tailed density functions. They have a nice hierarchical representation to make inferences easily. We propose the Sinh-normal/independent distribution which extends the Sinh-normal (SN) distribution [23]. We discuss some of its properties and propose the Sinh-normal/independent nonlinear regression model based on a similar setup of Lemonte and Cordeiro [18], who applied the Birnbaum-Saunders distribution. We develop an EM-algorithm for maximum likelihood estimation of the model parameters. In order to examine the robustness of this flexible class against outlying observations, we perform a simulation study and analyze a real data set to illustrate the usefulness of the new model.

Date: 2015
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DOI: 10.1080/02664763.2015.1005059

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