LEADER 05731nam 2200649 450 001 996466397003316 005 20230420164801.0 010 $a3-030-71175-7 024 7 $a10.1007/978-3-030-71175-7 035 $a(CKB)4100000011951205 035 $a(DE-He213)978-3-030-71175-7 035 $a(MiAaPQ)EBC6635755 035 $a(Au-PeEL)EBL6635755 035 $a(OCoLC)1255235127 035 $a(PPN)269152210 035 $a(EXLCZ)994100000011951205 100 $a20220131d2021 uy 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aAdvances in compositional data analysis $efestschrift in honour of Vera Pawlowsky-Glahn /$fPeter Filzmoser, Karel Hron, Josep Antoni Martín-Fernández, Javier Palarea-Albaladejo, editors 210 1$aCham, Switzerland :$cSpringer,$d[2021] 210 4$d©2021 215 $a1 online resource (XVIII, 404 p. 113 illus., 91 illus. in color.) 311 1 $a3-030-71174-9 311 1 $a9783030711740 320 $aIncludes bibliographical references. 327 $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. Fa?evicová, P. Kyn?lová and K. Mack?: Geographically weighted regression analysis for two-factorial compositional data -- C. Barceló-Vidal and J.A. Martín-Fernández: 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, À. 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. Martín-Fernández 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, ?. Pedi?i?, J. Palarea-Albaladejo, J.A. Martín-Fernández, K. Hron and T. Olds: Compositional data analysis in time-use epidemiology. 330 $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. 606 $aEstadística matemàtica$2lemac 606 $aInvestigació quantitativa$2lemac 606 $aMathematical statistics 606 $aQuantitative research 606 $aEstadística matemàtica$2thub 606 $aInvestigació quantitativa$2thub 608 $aLlibres electrònics$2thub 615 7$aEstadística matemàtica. 615 7$aInvestigació quantitativa. 615 0$aMathematical statistics. 615 0$aQuantitative research. 615 7$aEstadística matemàtica 615 7$aInvestigació quantitativa 676 $a519.5 701 $aPawlowsky-Glahn$b Vera$0741206 702 $aFilzmoser$b Peter 702 $aHron$b Karel 702 $aMarti?n-Ferna?ndez$b Josep Antoni 702 $aPalarea-Albadalejo$b Javier 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996466397003316 996 $aAdvances in compositional data analysis$92916997 997 $aUNISA