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001437190 001__ 1437190
001437190 003__ OCoLC
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001437190 019__ $$a1255465027
001437190 020__ $$a9783030711757$$q(electronic bk.)
001437190 020__ $$a3030711757$$q(electronic bk.)
001437190 020__ $$z9783030711740
001437190 0247_ $$a10.1007/978-3-030-71175-7$$2doi
001437190 035__ $$aSP(OCoLC)1255235127
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001437190 049__ $$aISEA
001437190 050_4 $$aQA276
001437190 08204 $$a519.5$$223
001437190 24500 $$aAdvances in compositional data analysis :$$bfestschrift in honour of Vera Pawlowsky-Glahn /$$cPeter Filzmoser, Karel Hron, Josep Antoni Martín-Fernández, Javier Palarea-Albaladejo, editors.
001437190 260__ $$aCham :$$bSpringer,$$c2021.
001437190 300__ $$a1 online resource (410 pages)
001437190 336__ $$atext$$btxt$$2rdacontent
001437190 337__ $$acomputer$$bc$$2rdamedia
001437190 338__ $$aonline resource$$bcr$$2rdacarrier
001437190 5050_ $$aPreface -- 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. Facevicova, P. Kynclova and K. Macku: Geographically weighted regression analysis for two-factorial compositional data -- C. Barcelo-Vidal and J.A. Martin-Fernandez: 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. SausSala, A. FarrerasNoguer, N. ArimanySerrat, 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. Martin-Fernandez 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, Z. Pedisic, J. Palarea-Albaladejo, J.A. Martin-Fernandez, K. Hron and T. Olds: Compositional data analysis in time-use epidemiology.
001437190 506__ $$aAccess limited to authorized users.
001437190 520__ $$aThis book presents modern methods and real-world applications of compositional data analysis. It covers a wide variety of topics, ranging from an updated presentation of basic concepts and ideas in compositional data analysis to recent advances in the context of complex data structures. Further, it illustrates real-world applications in numerous scientific disciplines and includes references to the latest software solutions available for compositional data analysis, thus providing a valuable and up-to-date guide for researchers and practitioners working with compositional data. Featuring selected contributions by leading experts in the field, the book is dedicated to Vera Pawlowsky-Glahn on the occasion of her 70th birthday.
001437190 588__ $$aDescription based on print version record.
001437190 650_0 $$aMathematical statistics.
001437190 650_0 $$aQuantitative research.
001437190 650_6 $$aRecherche quantitative.
001437190 655_7 $$aFestschriften.$$2fast$$0(OCoLC)fst01941036
001437190 655_7 $$aFestschriften.$$2lcgft
001437190 655_0 $$aElectronic books.
001437190 7001_ $$aFilzmoser, Peter.
001437190 7001_ $$aHron, Karel.
001437190 7001_ $$aMartín-Fernández, Josep Antoni.
001437190 7001_ $$aPalarea-Albaladejo, Javier.
001437190 7001_ $$aPawlowsky-Glahn, Vera,$$ehonouree.
001437190 77608 $$iPrint version:$$aFilzmoser, Peter.$$tAdvances in Compositional Data Analysis.$$dCham : Springer International Publishing AG, ©2021$$z9783030711740
001437190 852__ $$bebk
001437190 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-71175-7$$zOnline Access$$91397441.1
001437190 909CO $$ooai:library.usi.edu:1437190$$pGLOBAL_SET
001437190 980__ $$aBIB
001437190 980__ $$aEBOOK
001437190 982__ $$aEbook
001437190 983__ $$aOnline
001437190 994__ $$a92$$bISE