LEADER 05340nam 22005895 450 001 9910151661903321 005 20220418220054.0 010 $a3-319-44811-0 024 7 $a10.1007/978-3-319-44811-4 035 $a(CKB)3710000000952859 035 $a(DE-He213)978-3-319-44811-4 035 $a(MiAaPQ)EBC4746187 035 $a(PPN)197139140 035 $a(EXLCZ)993710000000952859 100 $a20161119d2016 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aCompositional data analysis $eCoDaWork, L?Escala, Spain, June 2015 /$fedited by Josep Antoni Martín-Fernández, Santiago Thió-Henestrosa 205 $a1st ed. 2016. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016. 215 $a1 online resource (X, 209 p. 71 illus., 58 illus. in color.) 225 1 $aSpringer Proceedings in Mathematics & Statistics,$x2194-1009 ;$v187 311 $a3-319-44810-2 320 $aIncludes bibliographical references at the end of each chapters. 327 $aCompositional Analysis of Species Composition - Pawlowsky-Glahn, Monreal-Pawlowsky, Egozcue -- Optimising Archaeologic Ceramics h-XRF Analyses - Bergman, Lindahl -- Relationship Between Popularity of Key Words on the Google Browser and the Evolution of Worldwide Financial Indexes - Ortells, Egozcue, Ortego, Garola -- Advances in Integrating Isotopic Data with Compositional Data Analysis: Applications for Deep Formation Brine Chemistry - Blondes, Engle, Geboy -- Space-time Compositional fields: An Introduction to Simplicial Partial Differential Operators - Jarauta-Bragulat, Egozcue -- A Compositional Approach to Allele Sharing Analysis - Galvan, Graffelman -- An Application of the Isometric Log-ratio Transformation in Relatedness Research -- Graffelman, Galvan -- Diagnostic Tools and Model Selection in Scaled-Dirichlet Regression - Monti, Mateu-Figueras, Pawlowsky-Glahn, Egozcue -- Toward the Concept of Background/Baseline Compositions: A Practicable Path? - Buccianti, Nisi, Raco -- Multi Element Geochemical Modelling for Mine Planning: Case Studies from Epithermal Gold Deposits ? Caciagli, Warman -- Recognizing and Validating Structural Processes in Geochemical Data - Grunsky, Kjarsgaard. 330 $aThe authoritative contributions gathered in this volume reflect the state of the art in compositional data analysis (CoDa). The respective chapters cover all aspects of CoDa, ranging from mathematical theory, statistical methods and techniques to its broad range of applications in geochemistry, the life sciences and other disciplines. The selected and peer-reviewed papers were originally presented at the 6th International Workshop on Compositional Data Analysis, CoDaWork 2015, held in L?Escala (Girona), Spain. Compositional data is defined as vectors of positive components and constant sum, and, more generally, all those vectors representing parts of a whole which only carry relative information. Examples of compositional data can be found in many different fields such as geology, chemistry, economics, medicine, ecology and sociology. As most of the classical statistical techniques are incoherent on compositions, in the 1980s John Aitchison proposed the log-ratio approach to CoDa. This became the foundation of modern CoDa, which is now based on a specific geometric structure for the simplex, an appropriate representation of the sample space of compositional data. The International Workshops on Compositional Data Analysis offer a vital discussion forum for researchers and practitioners concerned with the statistical treatment and modelling of compositional data or other constrained data sets and the interpretation of models and their applications. The goal of the workshops is to summarize and share recent developments, and to identify important lines of future research. 410 0$aSpringer Proceedings in Mathematics & Statistics,$x2194-1009 ;$v187 606 $aStatistics  606 $aGeochemistry 606 $aStatistical Theory and Methods$3https://scigraph.springernature.com/ontologies/product-market-codes/S11001 606 $aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/S17020 606 $aGeochemistry$3https://scigraph.springernature.com/ontologies/product-market-codes/G14003 606 $aStatistics for Life Sciences, Medicine, Health Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/S17030 615 0$aStatistics . 615 0$aGeochemistry. 615 14$aStatistical Theory and Methods. 615 24$aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. 615 24$aGeochemistry. 615 24$aStatistics for Life Sciences, Medicine, Health Sciences. 676 $a519.535 702 $aMartín-Fernández$b Josep Antoni$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aThió-Henestrosa$b Santiago$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910151661903321 996 $aCompositional data analysis$91347001 997 $aUNINA