Advances in Compositional Data Analysis

Preface.- J.J. Egozcue and W.L. Maldonado: An interpretable orthogonal decomposition of positive square matrices.- Part I Fundamentals.- I. Erb and N. Ay: The information-geometric perspective of compositional data analysis.- D.R. Lovell: Log-ratio analysis of finite precision data: caveats, and connections to digital lines and number theory.- G. Mateu-Figueras, G.S. Monti and J.J. Egozcue: Distributions on the simplex revisited.- J. Graffelman: Compositional biplots: a story of false leads and hidden features revealed by the last dimensions.- Part II Statistical Methodology.- K. FaÄevicov¡, P. KynÄlov¡ and K. Macků: Geographically weighted regression analysis for two-factorial compositional data.- C. Barcel³-Vidal and J.A. Mart­n-Fern¡ndez: Factor analysis of compositional data with a total.- M. Gallo, V. Simonacci and V. Todorov: A compositional three-way approach for student satisfaction analysis.- M. Templ: Artificial neural networks to impute rounded zeros in compositional data.- E. Saus-Sala, . Farreras-Noguer, N. Arimany-Serrat, and G. Coenders: Compositional du pont analysis. A visual tool for strategic financial performance assessment.- A. Menafoglio: Spatial statistics for distributional data in Bayes spaces: from object-oriented kriging to the analysis of warping functions.- C. Thomas-Agnan, T. Laurent, A. Ruiz-Gazen, N. Thi Huong An, R. Chakir and A. Lungarska: Spatial simultaneous autoregressive models for compositional data: application to land use.- Part III Applications.- A. Buccianti, C. Gozzi: The whole versus the parts: the challenge of compositional data analysis (CoDA) methods for geochemistry.- M.A. Engle and J.A. Chaput: Groundwater origin determination in historic chemical datasets through supervised compositional data analysis: Brines of the Permian Basin, USA.- J.M. McKinley, U. Mueller, P.M. Atkinson, U. Ofterdinger, S.F. Cox, R. Doherty, D. Fogarty and J.J. Egozcue.- Chronic kidney disease of uncertain aetiology and its relation with waterborne environmental toxins: An investigation via compositional balances.- R.A. Olea, J.A. Mart­n-Fern¡ndez and W.H. Craddock: Multivariate classification of the crude oil petroleum systems in southeast Texas, USA, using conventional and compositional data analysis of biomarkers.- J.R. Wu, J.M. Macklaim, B.L. Genge and G.B. Gloor: Finding the centre: compositional asymmetry in high-throughput sequencing datasets.- L. Huang and H. Li: Bayesian balance-regression in microbiome studies using stochastic search.- D.E. McGregor, P.M. Dall, J. Palarea-Albaladejo and S.F.M. Chastin: Compositional data analysis in physical activity and health research. Looking for the right balance.- D. Dumuid, Ž. PediÅ¡iÄ, J. Palarea-Albaladejo, J.A. Mart­n-Fern¡ndez, K. Hron and T. Olds: Compositional data analysis in time-use epidemiology.