The unit generalized half-normal quantile regression model: formulation, estimation, diagnostics, and numerical applications

Josmar Mazucheli, Mustafa Korkmaz, André F.B. Menezes, Víctor Leiva

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

In this paper, we propose and derive a new regression model for response variables defined on the open unit interval. By reparameterizing the unit generalized half-normal distribution, we get the interpretation of its location parameter as being a quantile of the distribution. In addition, we can evaluate effects of the explanatory variables in the conditional quantiles of the response variable as an alternative to the Kumaraswamy quantile regression model. The suitability of our proposal is demonstrated with two simulated examples and two real applications. For such data sets, the obtained fits of the proposed regression model are compared with that provided by a Kumaraswamy regression model.

Original languageEnglish
Pages (from-to)279-295
Number of pages17
JournalSoft Computing
Volume27
Issue number1
DOIs
StatePublished - Jan 2023

Keywords

  • Kumaraswamy distribution
  • Likelihood methods
  • Monte Carlo simulation
  • R software
  • Residual analysis
  • Unit generalized half-normal distribution

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