What's So Special About Semiparametric Methods?

Sankhya. Series B. [Methodological.] Pub Date : 2009-08-01
Michael R Kosorok
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Abstract

The number of scientific publications on semiparametric methods per year has been steadily increasing since the early 1980s. This increased interest has happened in spite of the fact that the novelty of semiparametrics for its own sake has run its course, and semiparametric methods are by now considered classical. The underlying reasons for this continued interest include the genuine scientific utility of semiparametric models combined with the breadth and depth of the many theoretical questions that remain to be answered. Empirical process techniques are an essential research tool for many of these questions. Moreover, both semiparametric methods and empirical processes are playing an increasingly valuable role in high dimensional data analysis and in other emerging areas in statistics. The topics are very fruitful and intriguing for new researchers to engage in. Graduate programs in statistics, biostatistics and econometrics can and should include more empirical processes and semiparametrics in their teaching in order to ensure a sufficient supply of suitably qualified researchers.

半参数方法有什么特别之处?
自20世纪80年代初以来,每年关于半参数方法的科学出版物的数量一直在稳步增加。尽管半参数本身的新颖性已经走完了它的历程,而且半参数方法现在被认为是经典的,但这种兴趣的增加还是发生了。这种持续兴趣的潜在原因包括半参数模型的真正科学效用,以及许多有待回答的理论问题的广度和深度。经验过程技术是许多这些问题的基本研究工具。此外,半参数方法和经验过程在高维数据分析和其他新兴统计领域中发挥着越来越有价值的作用。这些话题对于新的研究者来说是非常富有成果和有趣的。统计学、生物统计学和计量经济学的研究生课程可以而且应该在他们的教学中包括更多的经验过程和半参数,以确保有足够的合格研究人员。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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