Compositional Data
Biplots of compositional data
... Compositional data (Aitchison, 1986) consist of vectors of positive values summing to a unit, or in general to some ¯xed constant for all ...Such data arise in many disciplines, for example, in ...
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Distributional equivalence and subcompositional coherence in the analysis of contingency tables, ratio-scale measurements and compositional data
... for compositional data analysis, because if two components were always occurring in the same proportion in every sample, then the analysis should be unaffected by considering these two components ...
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A Hierarchical Bayesian Model for the Unmixing Analysis of Compositional Data subject to Unit-sum Constraints
... A generic problem in compositional data analysis is to extract the underlying independent sources from a large set of observational data. This linear mixing problem is common in audio, radio, and ...
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Fitness, fatness and the reallocation of time between children’s daily movement behaviours: an analysis of compositional data
... [20], compositional data can be transferred to the uncon- strained Real Space using a log-ratio ...sitional data are expressed as isometric log-ratio coordi- nates, conventional statistical methods ...
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Patterns of health behaviour associated with active travel: a compositional data analysis
... a compositional data analysis ap- proach to understanding the patterns of health behaviour associated with specific activities (such as active travel) can inform policy or interventions concerning that ...
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Improved classi cation for compositional data using the $\alpha$ transformation
... between compositional components (Greenacre, ...in compositional data analysis has been a matter of much debate; see for example the historical review and discussion in Scealy and Welsh ...
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The k NN algorithm for compositional data: a revised approach with and without zero values present
... An important issue in compositional data is the presence of zeros, which cause problems for the logarithmic transformation. The issue of zero values in some components is not addressed in most papers, but ...
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Local sensitivity analysis for compositional data with application to soil texture in hydrologic modelling
... of compositional data, the different components of the input are related through the closure balance, and conse- quently an OAT-SA on its individual components is not ...
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The single principle of compositional data analysis, continuing fallacies, confusions and misunderstandings and some suggested remedies
... Such transformations have been termed isometric logratio abbreviated to ilr. All this is admirable and provides simple theoretical results, particularly in establishing least square type properties of certain estimators. ...
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TIME SERIES ANALYSIS OF COMPOSITIONAL DATA USING A DYNAMIC LINEAR MODEL APPROACH
... of compositional data arises from the two inherent constraints mentioned ...raw compositional time se- ries ...transform data from the g- dimensional simplex to the g-dimensional real space R ...
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The Quality of Urban Air in Barcelona: A New Approach Applying Compositional Data Analysis Methods
... the compositional nature of the concentrations of air pollutants and do not apply methods of Compositional Data Analysis and have some other weak points such as leak of standardized ...on ...
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Dynamic graphics of parametrically linked multivariate methods used in compositional data analysis
... • The effect of the weighting can lead to dramatic improvements in the analysis of compositional data, because the influence of high log-ratios often present in rare components is reduced. The weighting ...
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Statistical Methods for High Dimensional Count and Compositional Data With Applications to Microbiome Studies
... to compositional data because the required regularity conditions are generally not ...of compositional variables is singular, thereby violating the usual assumptions on the eigenvalues of the ...
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Compositional data techniques for the analysis of the container traffic share in a multi-port region
... classes of proportional vectors quantifying shares. How- ever, it is usual to express them using a representative of the equivalence class, that is, applying the closure operation to them. CoDa vectors, turned into ...
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Spatial analysis of compositional data : a historical review
... developing compositional data analysis (CoDa) (Aitchison and Shen, 1980; Aitchison, 1982; Aitchison, 1986) introducing what nowa- days is known as the log-ratio ...of data to which geostatistics is ...
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Compositional Data Analysis is necessary for simulating and analyzing RNA-Seq data
... RNA-Seq data, the key 468 experimental step which requires a compositional approach is when the actual changes in the RNA content are 469 sampled using an equal but arbitrary amount of RNA by the library ...
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A data based power transformation for compositional data
... Two standard approaches to compositional data analysis, referred to in the paper as RDA and LRA, were discussed and compared. On the basis of simple numerical examples and further considerations we ...
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Compositional Data Analysis and Zeros in Micro Data
... of compositional data analysis methods in economics has some ...the data to be analyzed includes observa- tions where the observed budget share is ...of compositional data analysis to ...
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Exploring Compositional Data with the CoDa-Dendrogram
... of compositional data analysis (Aitchison, 1986; Aitchison and Egozcue, 2005; Egozcue, ...by compositional data are the ratios between the different parts of the observed ...the ...
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On the interpretation of differences between groups for compositional data
... Compositional data (CoDa) are quantitative descriptions of the parts or components of a whole, conveying exclusively relative ...and data from time use ...a data set X (n × D) using ...
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