Document details for 'zCompositions - R package for multivariate imputation of left-censored data under a compositional approach'

Authors Palarea Albaladejo, J. and Martin-Fernandez, J.A.
Publication details Chemometrics and Intelligent Laboratory Systems 143(2015), 85-96. Elsevier.
Publisher details Elsevier
Keywords Censored data; Nondetects; Zeros; Compositional data; Imputation; Log-ratio analysis
Abstract zCompositions is an R package for the imputation of left-censored data under a compositional approach. It is pertinent when the analyst assumes that the relevant information is contained on the relative variation structure of the data. For instance, in cases where the experimental data are simultaneously measured amounts related to a same total weight or volume. The approach is used in fields like geochemistry of waters or sedimentary rocks, environmental studies related to air pollution, physicochemical analysis of glass fragments in forensic science, among many others. In these fields, rounded zeros and nondetects are usually regarded as left-censored data that hamper any subsequent data analysis. The implemented methods consider aspects of relevance for a compositional approach such as scale invariance, subcompositional coherence or preserving the multivariate relative structure of the data. Based on solid statistical frameworks, it comprises the ability to deal with single and varying censoring thresholds, consistent treatment of closed and non-closed data, exploratory tools, multiple imputation, MCMC, robust and non-parametric alternatives, and recent proposals for count data. Key methodological aspects, new contributions, computational implementation and the practical application of the approach are discussed.
Last updated 2017-02-02

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