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Compositional Data Analysis Theory and Applications 1st Edition by Vera Pawlowsky Glahn, Antonella Buccianti 0470711353 9780470711354

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Compositional Data Analysis Theory and Applications 1st Edition Vera Pawlowsky-Glahn Digital Instant Download

Author(s): Vera Pawlowsky-Glahn, Antonella Buccianti
ISBN(s): 9780470711354, 0470711353
Edition: 1
File Details: PDF, 7.63 MB
Year: 2011
Language: english
SKU: EB-4538956 Category: Tags: ,

Compositional Data Analysis Theory and Applications 1st Edition by Vera Pawlowsky Glahn, Antonella Buccianti – Ebook PDF Instant Download/Delivery: 0470711353, 9780470711354

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Product details:

ISBN 10: 0470711353 

ISBN 13: 9780470711354

Author: Vera Pawlowsky Glahn, Antonella Buccianti

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.

Table of contents:

Part I : Introduction
CHAPTER 1: A Short History of Compositional Data Analysis
CHAPTER 2: Basic Concepts and Procedures

Part II : Theory – Statistical Modelling
CHAPTER 3: The Principle of Working on Coordinates
CHAPTER 4: Dealing with Zeros
CHAPTER 5: Robust Statistical Analysis
CHAPTER 6: Geostatistics for Compositions
CHAPTER 7: Compositional VARIMA Time Series
CHAPTER 8: Compositional Data and Correspondence Analysis
CHAPTER 9: Use of Survey Weights for the Analysis of Compositional Data
CHAPTER 10: Notes on the Scaled Dirichlet Distribution

Part III : Theory – Algebra and Calculus
CHAPTER 11: Elements of Simplicial Linear Algebra and Geometry
CHAPTER 12: Calculus of Simplex-Valued Functions
CHAPTER 13: Compositional Differential Calculus on the Simplex

Part IV : Applications
CHAPTER 14: Proportions, Percentages, PPM: Do the Molecular Biosciences Treat Compositional Data Right?
CHAPTER 15: Hardy–Weinberg Equilibrium: A Nonparametric Compositional Approach
CHAPTER 16: Compositional Analysis in Behavioural and Evolutionary Ecology
CHAPTER 17: Flying in Compositional Morphospaces: Evolution of Limb Proportions in Flying Vertebrates
CHAPTER 18: Natural Laws Governing the Distribution of the Elements in Geochemistry: The Role of the Log-Ratio Approach
CHAPTER 19: Compositional Data Analysis in Planetology: The Surfaces of Mars and Mercury
CHAPTER 20: Spectral Analysis of Compositional Data in Cyclostratigraphy
CHAPTER 21: Multivariate Geochemical Data Analysis in Physical Geography
CHAPTER 22: Combining Isotopic and Compositional Data: A Discrimination of Regions Prone to Nitrate Pollution
CHAPTER 23: Applications in Economics

Part V : Software
CHAPTER 24: Exploratory Analysis Using CoDaPack 3D
CHAPTER 25: robCompositions: An R-package for Robust Statistical Analysis of Compositional Data
CHAPTER 26: Linear Models with Compositions in R

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Tags: Vera Pawlowsky Glahn, Antonella Buccianti, Compositional, Applications