000764373 000__ 04821cam\a2200529Ii\4500
000764373 001__ 764373
000764373 005__ 20230306142413.0
000764373 006__ m\\\\\o\\d\\\\\\\\
000764373 007__ cr\cnunnnunnun
000764373 008__ 161122s2016\\\\sz\a\\\\o\\\\\100\0\eng\d
000764373 019__ $$a966564529
000764373 020__ $$a9783319448114$$q(electronic book)
000764373 020__ $$a3319448110$$q(electronic book)
000764373 020__ $$z9783319448107
000764373 035__ $$aSP(OCoLC)ocn963932179
000764373 035__ $$aSP(OCoLC)963932179$$z(OCoLC)966564529
000764373 040__ $$aN$T$$beng$$erda$$epn$$cN$T$$dIDEBK$$dEBLCP$$dGW5XE$$dYDX
000764373 049__ $$aISEA
000764373 050_4 $$aQA278
000764373 050_4 $$aQA276-280
000764373 08204 $$a519.5/35$$223
000764373 08204 $$a519.5
000764373 1112_ $$aCoDaWork (Conference)$$d(2015 :$$cLa Escala, Spain)
000764373 24510 $$aCompositional data analysis :$$bCoDaWork, L'Escala, Spain, June 2015 /$$cJosep Antoni Martín-Fernández, Santiago Thió-Henestrosa, editors.
000764373 2463_ $$aCoDoWork
000764373 264_1 $$aCham, Switzerland :$$bSpringer,$$c2016.
000764373 300__ $$a1 online resource (x, 209 pages) :$$billustrations.
000764373 336__ $$atext$$btxt$$2rdacontent
000764373 337__ $$acomputer$$bc$$2rdamedia
000764373 338__ $$aonline resource$$bcr$$2rdacarrier
000764373 4901_ $$aSpringer proceedings in mathematics & statistics,$$x2194-1009 ;$$vvolume 187
000764373 5050_ $$aForeword; Contents; Contributors; Optimising Archaeologic Ceramics h-XRF Analyses; 1 Introduction; 2 Experimental Design; 2.1 Measurements Below Detection Limit; 2.2 Assessing the Accuracy of the Measurements; 3 Analysis; 4 Conclusions and Future Research; References; A Practical Guide to the Use of Major Elements, Trace Elements, and Isotopes in Compositional Data Analysis: Applications for Deep Formation Brine Geochemistry; 1 Introduction; 2 Treatment of Isotopic Data for Compositional Data Analysis; 3 Interpretation of Isotopic Data Using Ilr Transformed Subcompositions
000764373 5058_ $$a4 The Simple Scaling Effect of Ilr Transformations on Low Log Ratio Variance (Isotope) or Low Concentration (Trace) Components5 Clr-Biplot Interpretation of Low Log Ratio Variance (Isotope) or Low Concentration (Trace) Components; 6 Discussion and Conclusions; References; Towards the Concept of Background/baseline Compositions: A Practicable Path?; 1 Introduction; 1.1 Background or Baseline: A Summary; 1.2 Baseline Hydrochemical (Compositional) Facies; 2 Materials and Methods; 2.1 Data Sources; 2.2 Statistical Methodologies; 3 Results and Discussion
000764373 5058_ $$a3.1 Sequential Binary Partition of Water Chemistry3.2 The Distributional Behaviour of Robust Mahalanobis Distance; 4 Conclusions; References; Multielement Geochemical Modelling for Mine Planning: Case Study from an Epithermal Gold Deposit; 1 Introduction; 2 Methodology; 2.1 Data Pre-processing; 2.2 rPCA; 2.3 k-Means Cluster Analysis; 2.4 Wireframes and Characterization of Domains; 3 Case Study; 3.1 Data and Data Pre-Processing; 3.2 rPCA; 3.3 k-means cluster analysis; 4 Conclusions; References; A Compositional Approach to Allele Sharing Analysis; 1 Introduction; 2 Identical by State Studies
000764373 5058_ $$a2.1 Example3 Identical by Descent Studies; 3.1 Examples; 4 Conclusion; References; An Application of the Isometric Log-Ratio Transformation in Relatedness Research; 1 Introduction; 2 Maximum Likelihood Estimation of IBD Probabilities; 3 Reparametrization of the Likelihood in Isometric Log-Ratios; 4 Examples; 5 Discussion; References; Recognizing and Validating Structural Processes in Geochemical Data: Examples from a Diamondiferous Kimberlite and a Regional Lake Sediment Geochemical Survey; 1 Introduction; 2 Methods; 2.1 Process Discovery; 2.2 Process Validation; 2.3 Geospatial Coherence
000764373 5058_ $$a3 Examples3.1 Process Discovery and Validation of Diamondiferous Kimberlites; 3.2 Predictive Mapping Regional Geology Using Lake Sediment Geochemistry; 4 Discussion; 5 Conclusions; References; Space-Time Compositional Models: An Introduction to Simplicial Partial Differential Operators; 1 Introduction; 2 Derivatives and Integrals of a Space-Time Simplicial Field; 3 Compositional Mass Continuity Equation and Differential Operators; 4 Conclusions; References; A Regression Model for Compositional Data Based on the Shifted-Dirichlet Distribution; 1 Introduction
000764373 506__ $$aAccess limited to authorized users.
000764373 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed December 5, 2016).
000764373 650_0 $$aMultivariate analysis$$vCongresses.
000764373 650_0 $$aCorrelation (Statistics)$$vCongresses.
000764373 7001_ $$aMartín-Fernández, Josep Antoni,$$eeditor.
000764373 7001_ $$aThió-Henestrosa, Santiago,$$eeditor.
000764373 830_0 $$aSpringer proceedings in mathematics & statistics ;$$vv. 187.
000764373 852__ $$bebk
000764373 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-44811-4$$zOnline Access$$91397441.1
000764373 909CO $$ooai:library.usi.edu:764373$$pGLOBAL_SET
000764373 980__ $$aEBOOK
000764373 980__ $$aBIB
000764373 982__ $$aEbook
000764373 983__ $$aOnline
000764373 994__ $$a92$$bISE