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Kumaraswamy regression model with Aranda-Ordaz link function

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Kumaraswamy regression model with Aranda-Ordaz link function. / Pumi, Guilherme; Rauber, Cristine; Bayer, Fábio M.
In: Test, Vol. 29, 01.12.2020, p. 1051–1071.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Pumi, G, Rauber, C & Bayer, FM 2020, 'Kumaraswamy regression model with Aranda-Ordaz link function', Test, vol. 29, pp. 1051–1071. https://doi.org/10.1007/s11749-020-00700-8

APA

Pumi, G., Rauber, C., & Bayer, F. M. (2020). Kumaraswamy regression model with Aranda-Ordaz link function. Test, 29, 1051–1071. https://doi.org/10.1007/s11749-020-00700-8

Vancouver

Pumi G, Rauber C, Bayer FM. Kumaraswamy regression model with Aranda-Ordaz link function. Test. 2020 Dec 1;29:1051–1071. Epub 2020 Jan 23. doi: 10.1007/s11749-020-00700-8

Author

Pumi, Guilherme ; Rauber, Cristine ; Bayer, Fábio M. / Kumaraswamy regression model with Aranda-Ordaz link function. In: Test. 2020 ; Vol. 29. pp. 1051–1071.

Bibtex

@article{6645cd9f7d5f4191bad8fa93cdc0833a,
title = "Kumaraswamy regression model with Aranda-Ordaz link function",
abstract = "In this work, we introduce a regression model for double-bounded variables in the interval (0, 1) following a Kumaraswamy distribution. The model resembles a generalized linear model, in which the response{\textquoteright}s median is modeled by a regression structure through the asymmetric Aranda-Ordaz parametric link function. We consider the maximum likelihood approach to estimate the regression and the link function parameters altogether. We study large sample properties of the proposed maximum likelihood approach, presenting closed-form expressions for the score vector as well as the observed and Fisher information matrices. We briefly present and discuss some diagnostic tools. We provide numeric evaluation of the finite sample inferences to show the performance of the estimators. Finally, to exemplify the usefulness of the methodology, we present and explore an empirical application.",
keywords = "Kumaraswamy distribution, Aranda-Ordaz link function, Regression model, Asymptotic theory, MLE",
author = "Guilherme Pumi and Cristine Rauber and Bayer, {F{\'a}bio M.}",
year = "2020",
month = dec,
day = "1",
doi = "10.1007/s11749-020-00700-8",
language = "English",
volume = "29",
pages = "1051–1071",
journal = "Test",

}

RIS

TY - JOUR

T1 - Kumaraswamy regression model with Aranda-Ordaz link function

AU - Pumi, Guilherme

AU - Rauber, Cristine

AU - Bayer, Fábio M.

PY - 2020/12/1

Y1 - 2020/12/1

N2 - In this work, we introduce a regression model for double-bounded variables in the interval (0, 1) following a Kumaraswamy distribution. The model resembles a generalized linear model, in which the response’s median is modeled by a regression structure through the asymmetric Aranda-Ordaz parametric link function. We consider the maximum likelihood approach to estimate the regression and the link function parameters altogether. We study large sample properties of the proposed maximum likelihood approach, presenting closed-form expressions for the score vector as well as the observed and Fisher information matrices. We briefly present and discuss some diagnostic tools. We provide numeric evaluation of the finite sample inferences to show the performance of the estimators. Finally, to exemplify the usefulness of the methodology, we present and explore an empirical application.

AB - In this work, we introduce a regression model for double-bounded variables in the interval (0, 1) following a Kumaraswamy distribution. The model resembles a generalized linear model, in which the response’s median is modeled by a regression structure through the asymmetric Aranda-Ordaz parametric link function. We consider the maximum likelihood approach to estimate the regression and the link function parameters altogether. We study large sample properties of the proposed maximum likelihood approach, presenting closed-form expressions for the score vector as well as the observed and Fisher information matrices. We briefly present and discuss some diagnostic tools. We provide numeric evaluation of the finite sample inferences to show the performance of the estimators. Finally, to exemplify the usefulness of the methodology, we present and explore an empirical application.

KW - Kumaraswamy distribution

KW - Aranda-Ordaz link function

KW - Regression model

KW - Asymptotic theory

KW - MLE

U2 - 10.1007/s11749-020-00700-8

DO - 10.1007/s11749-020-00700-8

M3 - Journal article

VL - 29

SP - 1051

EP - 1071

JO - Test

JF - Test

ER -