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  • 标题:Threshold Value Estimation Using Adaptive Two-Stage Plans in R
  • 本地全文:下载
  • 作者:Shawn Mankad ; George Michailidis ; Moulinath Banerjee
  • 期刊名称:Journal of Statistical Software
  • 印刷版ISSN:1548-7660
  • 电子版ISSN:1548-7660
  • 出版年度:2015
  • 卷号:67
  • 期号:1
  • 页码:1-19
  • 语种:English
  • 出版社:University of California, Los Angeles
  • 摘要:This paper introduces the R package twostageTE for estimation of an inverse regression function at a given point when one can sample an explanatory covariate at different values and measure the corresponding responses. The package implements a number of nonparametric methods for budget constrained threshold value estimation. Specifically, it contains methods for classical one-stage designs and also adaptive two-stage designs, which have been shown to yield more efficient and accurate results. A major advantage of the methods in package twostageTE is that threshold value estimation is performed without penalization or kernel smoothing, and hence, avoids the well-known problems of choosing the corresponding tuning parameter (regularization, bandwidth). The user can easily perform a two-stage analysis with twostageTE by (i) identifying the second stage sampling region from an initial sample, and (ii) computing various types of confidence intervals to ensure a robust analysis. The package twostageTE is illustrated through simulated examples.
  • 关键词:threshold estimation, two-stage estimation, R
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