Book description
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.
