DEALING WITH ZEROS AND MISSING VALUES IN COMPOSITIONAL DATA SETS USING NONPARAMETRIC IMPUTATION

dc.contributor.author	Martin-Fernandez J.A.
dc.contributor.author	Barcelo-Vidal C.
dc.contributor.author	Pawlowsky-Glahn V.
dc.date.accessioned	2022-01-25T05:52:45Z
dc.date.available	2022-01-25T05:52:45Z
dc.date.issued	2003
dc.identifier	https://elibrary.ru/item.asp?id=5005813
dc.identifier.citation	Mathematical Geology, 2003, 35, 3, 253-278
dc.identifier.issn	0882-8121
dc.identifier.uri	https://repository.geologyscience.ru/handle/123456789/34600
dc.description.abstract	The statistical analysis of compositional data based on logratios of parts is not suitable when zeros are present in a data set. Nevertheless, if there is interest in using this modeling approach, several strategies have been published in the specialized literature which can be used. In particular, substitution or imputation strategies are available for rounded zeros. In this paper, existing nonparametric imputation methods-both for the additive and the multiplicative approach-are revised and essential properties of the last method are given. For missing values a generalization of the multiplicative approach is proposed.
dc.subject	AITCHISON DISTANCE
dc.subject	DETECTION LIMIT
dc.subject	LOG-RATIO TRANSFORMATION
dc.subject	SIMPLEX, STRESS
dc.subject	THRESHOLD
dc.title	DEALING WITH ZEROS AND MISSING VALUES IN COMPOSITIONAL DATA SETS USING NONPARAMETRIC IMPUTATION
dc.type	Статья

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