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Approximate Confidence Intervals for Nonlinear Functions, With Applications to a Cloud-Seeding Experiment

 

作者: A.W. Davis,   L.G. Veitch,  

 

期刊: Technometrics  （Taylor Available online 1978）
卷期: Volume 20, issue 3  

页码: 227-230

 

ISSN:0040-1706

 

年代: 1978

 

DOI:10.1080/00401706.1978.10489665

 

出版商: Taylor & Francis Group

 

关键词: Approximate confidence limits;Cloud seeding;Fiducial distribution;Bayesian posterior distribution;Monte Carlo methods

 

数据来源: Taylor

 

摘要:

As an expedient for constructing approximate confidence intervals for complicated parametric functions, it is suggested that fiducial or Bayes intervals be generated by Monte Carlo methods. In each application these may be empirically tested for their frequency properties. The method was applied to the overall seeding effect in a rainfall modification experiment, and it is concluded that a useful approximate confidence interval was obtained.

 

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