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

被引:11
|
作者
Mazucheli, Josmar [1 ]
Korkmaz, Mustafa C. [2 ]
Menezes, Andre F. B. [3 ]
Leiva, Victor [4 ]
机构
[1] Univ Estadual Maringa, Dept Stat, Maringa, Parana, Brazil
[2] Artvin Coruh Univ, Dept Measurement & Evaluat, Artvin, Turkey
[3] Univ Estadual Campinas, Dept Stat, Campinas, SP, Brazil
[4] Pontificia Univ Catolica Valparaiso, Sch Ind Engn, Valparaiso, Chile
关键词
Kumaraswamy distribution; Likelihood methods; Monte Carlo simulation; R software; Residual analysis; Unit generalized half-normal distribution; LINDLEY DISTRIBUTION; POWER DISTRIBUTION; BETA REGRESSION;
D O I
10.1007/s00500-022-07278-3
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:279 / 295
页数:17
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