The Statistical Analysis of Compositional Data (Monographs on Statistics & Applied Probability)

Aitchson, J.

ISBN 10: 0412280604 / ISBN 13: 9780412280603

Edité par Chapman And Hall, 1986

A propos de cet article

This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In fair condition, suitable as a study copy. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,750grams, ISBN:0412280604.

N° de réf. du vendeur 8614919

Détails bibliographiques

• Titre: The Statistical Analysis of Compositional Data (Monographs on Statistics & Applied Probability)
• Éditeur: Chapman And Hall
• Date de parution: 1986
• Langue: anglais
• ISBN à 10 chiffres: 0412280604
• ISBN à 13 chiffres: 9780412280603
• Reliure: Couverture rigide
• État de l'article: Fair
• Catalogues du vendeur:
  • Mathematics

A propos de ce titre

Synopsis

As long ago as 1897 Karl Pearson, in a now classic paper on spurious correlation, first pointed out dangers that may befall the analyst who attempts to interpret correlations between ratios whose numerators and denominators contain common parts. He thus implied that the analysis of compositional data, with its concentration on relation- ships between proportions of some whole, is likely to be fraught with difficulty. History has proved him correct: over the succeeding years and indeed right up to the present day, there has been no other form of data analysis where more confusion has reigned and where more improper and inadequate statistical methods have been applied. The special and intrinsic feature of compositional data is that the proportions of a composition are naturally subject to a unit-sum constraint. For other forms of constrained data, in particular for directional data where there is a unit-length constraint on each direction vector, scientist and statistician alike have readily appre- ciated that new statistical methods, appropriate to the special nature of the data, are required; and there now exists an extensive literature on the successful statistical analysis of directional data. It is paradox- ical that for compositional data, subject to an apparently simpler constraint, such an appreciation and development have been slower to emerge. In applications the unit-sum constraint has been widely ignored or wished away and inappropriate 'standard' statistical methods, devised for and successfully applied to unconstrained data, have been used with disastrous consequences.