02721nam 2200673 a 450 991013322130332120240514071514.01-283-20451-797866132045161-119-97646-41-119-97647-2(CKB)3400000000015962(EBL)819260(OCoLC)746321035(SSID)ssj0000535277(PQKBManifestationID)11379278(PQKBTitleCode)TC0000535277(PQKBWorkID)10523093(PQKB)10216201(MiAaPQ)EBC819260(Au-PeEL)EBL819260(CaPaEBR)ebr10488528(CaONFJC)MIL320451(PPN)185060498(EXLCZ)99340000000001596220110505d2011 uy 0engurcn|||||||||txtccrCompositional data analysis theory and applications /edited by Vera Pawlowsky-Glahn, Antonella Buccianti1st ed.Hoboken, N.J. Wiley20111 online resource (402 p.)Description based upon print version of record.1-119-97761-4 0-470-71135-3 Includes bibliographical references and index.pt. 1. Introduction -- pt. 2. Theory-- statistical modelling -- pt. 3. Theory-- algebra and calculus -- pt. 4. Applications -- pt. 5. Software.It is difficult to imagine that the statistical analysis of compositional data has been a major issue of concern for more than 100 years. It is even more difficult to realize that so many statisticians and users of statistics are unaware of the particular problems affecting compositional data, as well as their solutions. The issue of ``spurious correlation'', as the situation was phrased by Karl Pearson back in 1897, affects all data that measures parts of some whole, such as percentages, proportions, ppm and ppb. Such measurements are present in all fields of science, ranging from geology, biMultivariate analysisCorrelation (Statistics)Anàlisi multivariablelemacCorrelació (Estadística)lemacMultivariate analysis.Correlation (Statistics)Anàlisi multivariableCorrelació (Estadística)519.5/35Pawlowsky-Glahn Vera741206Buccianti Antonella147009MiAaPQMiAaPQMiAaPQBOOK9910133221303321Compositional data analysis2207468UNINA