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BookDOI

Compositional data analysis : theory and applications

TLDR
This book presents the history and development of compositional data analysis along with Aitchison's log-ratio approach, and describes the state of the art both in theoretical fields as well as applications in the different fields of science.
Abstract
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.

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Journal ArticleDOI

Inferring Correlation Networks from Genomic Survey Data

TL;DR: SparCC as mentioned in this paper is a new approach that is capable of estimating correlation values from compositional data, which is used to infer a rich ecological network connecting hundreds of interacting species across 18 sites on the human body.
Journal ArticleDOI

Combined Effects of Time Spent in Physical Activity, Sedentary Behaviors and Sleep on Obesity and Cardio-Metabolic Health Markers: A Novel Compositional Data Analysis Approach

TL;DR: Time spent in MVPA is an important target for intervention and preventing transfer of time from LIPA to SB might lessen the negative effects of physical inactivity, so time spent in each of these behaviors are codependent.
Posted Content

Bayesian Stable Isotope Mixing Models

TL;DR: In this article, stable isotope mixing models (SIMMs) are used to quantify the proportional contributions of various sources to a mixture, and a compositional component of the model is based on the isometric log ratio (ilr) transform of Egozcue (2003).
Journal ArticleDOI

zCompositions — R package for multivariate imputation of left-censored data under a compositional approach

TL;DR: zCompositions as discussed by the authors is an R package for the imputation of left-censored data under a compositional approach, which is used in fields like geochemistry of waters or sedimentary rocks, environmental studies related to air pollution, physicochemical analysis of glass fragments in forensic science.
Journal ArticleDOI

Bayesian stable isotope mixing models

TL;DR: This paper proposes a compositional mixture of the food sources corrected for various metabolic factors based on the isometric log‐ratio transform, which can apply a range of time series and non‐parametric smoothing relationships.
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Related Papers (5)