平坦似然:三参数WEIBULL模型情形

Q4 Computer Science
J. Montoya, Gudelia Figueroa-Preciado
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引用次数: 0

摘要

当似然函数形状变得平坦时,对最大似然估计的批评经常发生。尽管已经对平坦可能性的可能原因进行了一些研究,但还需要更多的工作来扩展我们对这一主题的了解。本文分析了威布尔平坦似然的起源。特别是,当三参数威布尔阈值参数变为无穷大时,我们通过检查相对轮廓似然的极限行为来研究似然平坦性的严重性。在这里讨论的情况下,平坦似然不仅与样本大小有关,还与嵌入模型问题有关。由于似然函数在推理统计方法中的广泛使用,重要的是不仅要识别可能导致平坦似然的因素,还要研究这种平坦的严重性,以便开发或应用特殊的统计和计算方法进行推理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
FLAT LIKELIHOODS: THREE-PARAMETER WEIBULL MODEL CASE
Criticisms of maximum likelihood estimation frequently occur when likelihood function shape becomes flat. Although some research have been done regarding the possible causes of a flat likelihood, more work is needed to expand our knowledge on this subject. In this paper we analyze the origin of Weibull flat likelihoods. In particular, we study the severity of the likelihood flatness by examining the limit behaviour of the relative profile likelihood for the three-parameter Weibull threshold parameter, when this parameter goes to infinity. In the cases discussed here, flat likelihoods are not only related to sample size but also to an embedded model problem. Due to the widespread use of the likelihood function in inferential statistical methods, it is important not only to identify factors that can cause flat likelihoods, but also to study the severity of this flattening, in order to develop or apply ad hoc statistical and computational methods for making inferences.
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来源期刊
CiteScore
0.40
自引率
0.00%
发文量
6
审稿时长
10 weeks
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