Discriminating Among Several Semiparametric Models

M. M. E. Abd El-Monsef; M. M. Seyam

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Discriminating Among Several Semiparametric Models

机译：在几种半甲型模型中区分

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To distinguish between two or more than two models one can use the T-optimality criterion. Another criterion using for discrimination between two or more than two models is KL-criterion, which depend on the Kullback-Leibler distance. KL-criterion can be used to discriminate between two non-normal models and a generalized of the KL-criterion was studied to discriminate more than two non-normal models. In this paper, more than two semiparametric models can be distinguished using generalized KL-criterion. An application was applied to illustrate the proposed technique by using three proportional hazard models via real data.

机译：要区分两个或两个以上模型，可以使用T-Optimaly标准。使用两种或两种以上模型之间的识别的另一标准是KL标准，这取决于kullback-leibler距离。 KL-Criterion可用于区分两个非正常模型，并研究了KL标准的广义，以区分了两个以上的非正常模型。在本文中，可以使用广义的KL标准来区分两种以上的半游戏模型。应用应用于通过使用真实数据使用三种比例危险模型来说明所提出的技术。

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《International Journal of Statistics and Probability》 |2013年第3期|共5页
作者
M. M. E. Abd El-Monsef; M. M. Seyam;
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中图分类概率论与数理统计;
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Discriminating Among Several Semiparametric Models

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