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  • 标题:Maximum Likelihood Method for Predicting Environmental Conditions from Assemblage Composition: The R Package bio.infer
  • 本地全文:下载
  • 作者:Lester L. Yuan
  • 期刊名称:Journal of Statistical Software
  • 印刷版ISSN:1548-7660
  • 电子版ISSN:1548-7660
  • 出版年度:2007
  • 卷号:22
  • 期号:1
  • 页码:1-20
  • 语种:English
  • 出版社:University of California, Los Angeles
  • 摘要:This paper provides a brief introduction to the R package bio.infer, a set of scripts that facilitates the use of maximum likelihood (ML) methods for predicting environmental conditions from assemblage composition. Environmental conditions can often be inferred from only biological data, and these inferences are useful when other sources of data are unavailable. ML prediction methods are statistically rigorous and applicable to a broader set of problems than more commonly used weighted averaging techniques. However, ML methods require a substantially greater investment of time to program algorithms and to perform computations. This package is designed to reduce the effort required to apply ML prediction methods.
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