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Goodness-of-fit tests via (φ)-measures of divergence for censored data

机译:通过(φ)量度的被审查数据进行拟合优度检验

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摘要

Measures of divergence or discrepancy are used extensively in statistics in various fields. In this article, we are focusing on divergence measures that are based on a class of measures known as Csiszar's divergence measures. In particular, we propose a class of goodness-of-fit tests based on Csiszar's class of measures designed for censored survival or reliability data. Further, we derive the asymptotic distribution of the test statistic under simple and composite null hypotheses as well as under contiguous alternative hypotheses. Simulations are furnished and real data are analysed to show the performance of the proposed tests for different (φ)-divergence measures.
机译:差异或差异的度量广泛用于各个领域的统计中。在本文中,我们将重点放在基于一类称为Csiszar分歧度量的度量的差异度量上。尤其是,我们根据Csiszar为检查生存率或可靠性数据而设计的一类措施,提出了一类拟合优度测试。此外,我们推导了简单和复合零假设下以及连续替代假设下的检验统计量的渐近分布。提供了仿真并分析了实际数据,以显示针对不同(φ)发散度量的建议测试的性能。

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