β回归模型的R2型调整度量

IF 0.6 Q4 STATISTICS & PROBABILITY
S. W. Mahmood, Noor Nawzat Seyala, Z. Algamal
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引用次数: 5

摘要

r2测度,即决定系数,通常被用作评价回归模型预测能力的工具。然而,这种基于广义线性模型偏差的度量对小样本很敏感。因此,有必要根据协变量的数量调整r2测度。Beta回归模型在比例或比率数据建模方面受到了许多科学领域的关注。本文在beta回归模型中提出了几个调整后的r2测度。通过仿真和实际数据应用,对所提措施的性能进行了评价。结果表明,与其他措施相比,所提出的措施具有优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adjusted R2 - type measures for beta regression model
R 2 measure, which named coefficient of determination, is usually used as tools for evaluation the predictive power of the regression models. However, this measure, which is based on deviance for generalized linear models, is sensitive to the small samples. Therefore, it is necessary to adjust R 2 measure according to the number of covariates. Beta regression model has received much attention in several science fields in modeling proportions or rates data. In this paper, several adjusted R 2 measures are proposed in beta regression models. The performance of the proposed measures is evaluated through simulation and real data application. Results demonstrate the superiority of the proposed measures compared to others.
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来源期刊
CiteScore
1.40
自引率
14.30%
发文量
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