【作者(必填)】

• Vera Pawlowsky‐Glahn
• Antonella Bucciant
  

【文题(必填)】
Compositional Data Analysis: Theory and Applications
【年份(必填)】
28 July 2011
【全文链接或数据库名称(选填)】
https://onlinelibrary.wiley.com/doi/book/10.1002/9781119976462

About this book      It is difficult to imagine that the statistical analysis of compositional data has         been a major issue of concern for more than 100 years. It is even more difficult to         realize that so many statisticians and users of statistics are unaware of the particular         problems affecting compositional data, as well as their solutions. The issue of ``spurious         correlation'', as the situation was phrased by Karl Pearson back in 1897, affects         all data that measures parts of some whole, such as percentages, proportions, ppm         and ppb. Such measurements are present in all fields of science, ranging from geology,         biology, environmental sciences, forensic sciences, medicine and hydrology. This         book presents the history and development of compositional data analysis along with         Aitchison's log-ratio approach. Compositional Data Analysis describes the state         of the art both in theoretical fields as well as applications in the different fields         of science.

Key Features:

• Reflects the state-of-the-art         in compositional data analysis.
• Gives an overview of the historical development         of compositional data analysis, as well as basic concepts and procedures.
• Looks         at advances in algebra and calculus on the simplex.
• Presents applications         in different fields of science, including, genomics, ecology, biology, geochemistry,         planetology, chemistry and economics.
• Explores connections to correspondence         analysis and the Dirichlet distribution.
• Presents a summary of three available         software packages for compositional data analysis.
• Supported by an accompanying         website featuring R code.
  

Applied scientists working on compositional         data analysis in any field of science, both in academia and professionals will benefit         from this book, along with graduate students in any field of science working with         compositional data.