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 we
Compositional Data Analysis: Theory and Applications
- Year
- 2011
- Tongue
- English
- Leaves
- 390
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
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.Content:
Chapter 1 A Short History of Compositional Data Analysis (pages 1β11): John Bacon?Shone
Chapter 2 Basic Concepts and Procedures (pages 12β28): Juan Jose Egozcue and Vera Pawlowsky?Glahn
Chapter 3 The Principle of Working on Coordinates (pages 29β42): Gloria Mateu?Figueras, Vera Pawlowsky?Glahn and Juan Jose Egozcue
Chapter 4 Dealing with Zeros (pages 43β58): Josep Antoni Martin?Fernandez, Javier Palarea?Albaladejo and Ricardo Antonio Olea
Chapter 5 Robust Statistical Analysis (pages 59β72): Peter Filzmoser and Karel Hron
Chapter 6 Geostatistics for Compositions (pages 73β86): Raimon Tolosana?Delgado, Karl Gerald van den Boogaart and Vera Pawlowsky?Glahn
Chapter 7 Compositional VARIMA Time Series (pages 87β103): Carles Barcelo?Vidal, Lucia Aguilar and Josep Antoni Martin?Fernandez
Chapter 8 Compositional Data and Correspondence Analysis (pages 104β113): Michael Greenacre
Chapter 9 Use of Survey Weights for the Analysis of Compositional Data (pages 114β127): Monique Graf
Chapter 10 Notes on the Scaled Dirichlet Distribution (pages 128β138): Gianna Serafina Monti, Gloria Mateu?Figueras and Vera Pawlowsky?Glahn
Chapter 11 Elements of Simplicial Linear Algebra and Geometry (pages 139β157): Juan Jose Egozcue, Carles Barcelo?Vidal, Josep Antoni Martin?Fernandez, Eusebi Jarauta?Bragulat, Jose Luis Diaz?Barrero and Gloria Mateu?Figueras
Chapter 12 Calculus of Simplex?Valued Functions (pages 158β175): Juan Jose Egozcue, Eusebi Jarauta?Bragulat and Jose Luis Diaz?Barrero
Chapter 13 Compositional Differential Calculus on the Simplex (pages 176β190): Carles Barcelo?Vidal, Josep Antoni Martin?Fernandez and Gloria Mateu?Figueras
Chapter 14 Proportions, Percentages, PPM: Do the Molecular Biosciences Treat Compositional Data Right? (pages 191β207): David Lovell, Warren Muller, Jen Taylor, Alec Zwart and Chris Helliwell
Chapter 15 HardyβWeinberg Equilibrium: A Nonparametric Compositional Approach (pages 208β217): Jan Graffelman and Juan Jose Egozcue
Chapter 16 Compositional Analysis in Behavioural and Evolutionary Ecology (pages 218β234): Michele Edoardo Raffaele Pierotti and Josep Antoni Martin?Fernandez
Chapter 17 Flying in Compositional Morphospaces: Evolution of Limb Proportions in Flying Vertebrates (pages 235β254): Luis Azevedo Rodrigues, Josep Daunis?i?Estadella, Gloria Mateu?Figueras and Santiago Thio?Henestrosa
Chapter 18 Natural Laws Governing the Distribution of the Elements in Geochemistry: The Role of the Log?Ratio Approach (pages 255β266): Antonella Buccianti
Chapter 19 Compositional Data Analysis in Planetology: The Surfaces of Mars and Mercury (pages 267β281): Helmut Lammer, Peter Wurz, Josep Antoni Martin?Fernandez and Herbert Iwo Maria Lichtenegger
Chapter 20 Spectral Analysis of Compositional Data in Cyclostratigraphy (pages 282β289): Eulogio Pardo?Iguzquiza and Javier Heredia
Chapter 21 Multivariate Geochemical Data Analysis in Physical Geography (pages 290β301): Jennifer McKinley and Christopher David Lloyd
Chapter 22 Combining Isotopic and Compositional Data: A Discrimination of Regions Prone to Nitrate Pollution (pages 302β317): Roger Puig, Raimon Tolosana?Delgado, Neus Otero and Albert Folch
Chapter 23 Applications in Economics (pages 318β326): Tim Fry
Chapter 24 Exploratory Analysis Using CoDaPack 3D (pages 327β340): Santiago Thio?Henestrosa and Josep Daunis?i?Estadella
Chapter 25 robCompositions: An R?package for Robust Statistical Analysis of Compositional Data (pages 341β355): Matthias Templ, Karel Hron and Peter Filzmoser
Chapter 26 Linear Models with Compositions in R (pages 356β371): Raimon Tolosana?Delgado and Karl Gerald van den Boogaart
π SIMILAR VOLUMES
With the advent of the Web along with the unprecedented amount of information available in electronic format, conceptual data analysis is more useful and practical than ever, because this technology addresses important limitations of the systems that currently support users in their quest for inform
<p>The aim of this book is to provide an internationally respected collection of scientific research methods, technologies and applications in the area of data science. This book can prove useful to the researchers, professors, research students and practitioners as it reports novel research work on
<p>The aim of this book is to provide an internationally respected collection of scientific research methods, technologies and applications in the area of data science. This book can prove useful to the researchers, professors, research students and practitioners as it reports novel research work on
<p>The aim of this book is to provide an internationally respected collection of scientific research methods, technologies and applications in the area of data science. This book can prove useful to the researchers, professors, research students and practitioners as it reports novel research work on