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

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 ev...

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Bibliographic Details
Published inSoft computing (Berlin, Germany) Vol. 27; no. 1; pp. 279 - 295
Main Authors Mazucheli, Josmar, Korkmaz, Mustafa Ç., Menezes, André F. B., Leiva, Víctor
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2023
Subjects
Artificial Intelligence
Computational Intelligence
Control
Engineering
Mathematical Logic and Foundations
Mathematical Methods in Data Science
Mechatronics
Robotics
Unit generalized half-normal distribution
Residual analysis
R software
Kumaraswamy distribution
Likelihood methods
Monte Carlo simulation
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Summary: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.
Bibliography:ObjectType-Article-1
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ISSN:1432-7643
1433-7479
DOI:10.1007/s00500-022-07278-3