(2021) Kumaraswamy regression modeling for Bounded Outcome Scores. Pakistan Journal of Statistics and Operation Research. pp. 79-88. ISSN 1816-2711
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Abstract
In this paper, we use a regression model for modeling bounded outcome scores (BOS), where the outcome is Kumaraswamy distributed. Similar to the Beta distribution, this distribution can take a variety of shapes while being computationally easier to use. Thus, it is deemed as a suitable alternative distribution to the Beta in modeling bounded random processes. In the proposed model, the median of a bounded response is modeled by the linear predictors which are defined through regression parameters and explanatory variables. We obtained the maximum likelihood estimates (MLEs) of the parameters, provided closed-form expressions for the score functions and Fisher information matrix, and presented some diagnostic measures. We conducted Monte Carlo simulations to investigate the finite-sample performance of the MLEs of the parameters. Finally, two practical applications of this model to the real data sets are presented and discussed.
Item Type: | Article |
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Keywords: | Bounded outcome score Kumaraswamy distribution Beta regression maximum likelihood estimation diagnostic analysis beta regression Mathematics |
Divisions: | |
Page Range: | pp. 79-88 |
Journal or Publication Title: | Pakistan Journal of Statistics and Operation Research |
Volume: | 17 |
Number: | 1 |
Identification Number: | 10.18187/pjsor.v17i1.3411 |
ISSN: | 1816-2711 |
Depositing User: | مهندس مهدی شریفی |
URI: | http://eprints.zbmu.ac.ir/id/eprint/3365 |
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