zCompositions-package: Treatment of zeros and nondetects in compositional data sets

In zCompositions: Treatment of Zeros, Left-Censored and Missing Values in Compositional Data Sets

Treatment of zeros and nondetects in compositional data sets

Description

Following compositional data analysis principles, this package provides simple and friendly tools to explore and impute zeros, left-censored (such as rounded zeros or values below single or multiple limits of detection; a.k.a nondetects) and missing data; including zero pattern/group-wise data analysis and testing procedures.

Details

Package:	zCompositions
Type:	Package
Version:	1.4.1
Date:	2023-08-23
License:	GPL (>= 2)

Author(s)

Javier Palarea-Albaladejo and Josep Antoni Martin-Fernandez

Maintainer: Javier Palarea-Albaladejo <[e-mail]>

References

Martin-Fernandez, J.A., Barcelo-Vidal, C., Pawlowsky-Glahn, V., 2003. Dealing with zeros and missing values in compositional data sets using nonparametric imputation. Mathematical Geology 35 (3): 253-27.

Martin-Fernandez, J.A., Hron, K., Templ, M., Filzmoser, P., Palarea-Albaladejo, J., 2012. Model-based replacement of rounded zeros in compositional data: Classical and robust approaches. Computational Statistics and Data Analysis 56: 2688-2704.

Martin-Fernandez, J.A., Hron, K., Templ, M., Filzmoser, P., Palarea-Albaladejo, J., 2015. Bayesian-multiplicative treatment of count zeros in compositional data sets. Statistical Modelling 15 (2): 134-158.

Palarea-Albaladejo, J., Martin-Fernandez, J.A., Gomez-Garcia, J., 2007. A parametric approach for dealing with compositional rounded zeros. Mathematical Geology 39 (7): 625-645.

Palarea-Albaladejo, J., Martin-Fernandez, J.A., 2008. A modified EM alr-algorithm for replacing rounded zeros in compositional data sets. Computers & Geosciences 34 (8): 902-917.

Palarea-Albaladejo, J., Martin-Fernandez, J.A., 2013. Values below detection limit in compositional chemical data. Analytica Chimica Acta 764: 32-43.

Palarea-Albaladejo, J., Martin-Fernandez J.A., Olea, R.A., 2014. A bootstrap estimation scheme for chemical compositional data with nondetects. Journal of Chemometrics 28: 585-599.

Palarea-Albaladejo J. and Martin-Fernandez J.A., 2015. zCompositions – R package for multivariate imputation of left-censored data under a compositional approach. Chemometrics and Intelligent Laboratory Systems 143: 85-96.

Palarea-Albaladejo, J, Antoni Martín-Fernández, J, Ruiz-Gazen, A, Thomas-Agnan, C., 2022. lrSVD: An efficient imputation algorithm for incomplete high-throughput compositional data. Journal of Chemometrics 36: e3459.

See Also

Aitchison, J., 1986. The Statistical Analysis of Compositional Data. Monographs on Statistics and Applied Probability. Chapman and Hall Ltd., London, UK (re-edited in 2003 with additional material).

Filzmoser, P., Hron, K., Templ, M., 2018. Applied Compositional Data Analysis. With Worked Examples in R. Springer, Switzerland.

Filzmoser P., Hron K., Martín-Fernández J.A., Palarea-Albaladejo J. (eds.), 2021. Advances in Compositional Data Analysis. Springer, Cham.

Pawlowsky-Glahn, V., Buccianti, A. (Eds.), 2011. Compositional Data Analysis: Theory and Applications. John Wiley & Sons, Ltd., Chichester,UK.

Pawlowsky-Glahn, V., Egozcue, J.J., Tolosana-Delgado, R., 2015. Modeling and analysis of compositional data. John Wiley & Sons, Ltd., Chichester, UK.

van den Boogaart, K.G., Tolosana-Delgado, R., 2013, Analyzing Compositional Data with R. Springer-Verlag, Berlin, Germany.

zCompositions documentation built on Aug. 24, 2023, 1:08 a.m.