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https://doi.org/10.21256/zhaw-22472| Publication type: | Article in scientific journal |
| Type of review: | Peer review (publication) |
| Title: | Classical and robust regression analysis with compositional data |
| Authors: | van den Boogaart, K.G. Filzmoser, P. Hron, K. Templ, M. Tolosano-Delgado, R. |
| et. al: | No |
| DOI: | 10.1007/s11004-020-09895-w 10.21256/zhaw-22472 |
| Published in: | Mathematical Geosciences |
| Volume(Issue): | 53 |
| Issue: | 5 |
| Page(s): | 823 |
| Pages to: | 858 |
| Issue Date: | 6-Oct-2020 |
| Publisher / Ed. Institution: | Springer |
| ISSN: | 1874-8961 1874-8953 |
| Language: | English |
| Subjects: | Balances; Robust regression; GEMAS project; Hypothesis testing; Robust bootstrap |
| Subject (DDC): | 510: Mathematics |
| Abstract: | Compositional data carry their relevant information in the relationships (logratios) between the compositional parts. It is shown how this source of information can be used in regression modeling, where the composition could either form the response, or the explanatory part, or even both. An essential step to set up a regression model is the way how the composition(s) enter the model. Here, balance coordinates will be constructed that support an interpretation of the regression coefficients and allow for testing hypotheses of subcompositional independence. Both classical least-squares regression and robust MM regression are treated, and they are compared within different regression models at a real data set from a geochemical mapping project. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/22472 |
| Fulltext version: | Published version |
| License (according to publishing contract): | CC BY 4.0: Attribution 4.0 International |
| Departement: | School of Engineering |
| Organisational Unit: | Institute of Data Analysis and Process Design (IDP) |
| Appears in collections: | Publikationen School of Engineering |
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|---|---|---|---|---|
| 2020_van-den-Boogaart-etal_Classical-and-robust-regression-analysis-with-compositional-data.pdf | 1.86 MB | Adobe PDF |  View/Open |
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van den Boogaart, K. G., Filzmoser, P., Hron, K., Templ, M., & Tolosano-Delgado, R. (2020). Classical and robust regression analysis with compositional data. Mathematical Geosciences, 53(5), 823–858. https://doi.org/10.1007/s11004-020-09895-w
van den Boogaart, K.G. et al. (2020) ‘Classical and robust regression analysis with compositional data’, Mathematical Geosciences, 53(5), pp. 823–858. Available at: https://doi.org/10.1007/s11004-020-09895-w.
K. G. van den Boogaart, P. Filzmoser, K. Hron, M. Templ, and R. Tolosano-Delgado, “Classical and robust regression analysis with compositional data,” Mathematical Geosciences, vol. 53, no. 5, pp. 823–858, Oct. 2020, doi: 10.1007/s11004-020-09895-w.
VAN DEN BOOGAART, K.G., P. FILZMOSER, K. HRON, M. TEMPL und R. TOLOSANO-DELGADO, 2020. Classical and robust regression analysis with compositional data. Mathematical Geosciences. 6 Oktober 2020. Bd. 53, Nr. 5, S. 823–858. DOI 10.1007/s11004-020-09895-w
van den Boogaart, K.G., P. Filzmoser, K. Hron, M. Templ, and R. Tolosano-Delgado. 2020. “Classical and Robust Regression Analysis with Compositional Data.” Mathematical Geosciences 53 (5): 823–58. https://doi.org/10.1007/s11004-020-09895-w.
van den Boogaart, K. G., et al. “Classical and Robust Regression Analysis with Compositional Data.” Mathematical Geosciences, vol. 53, no. 5, Oct. 2020, pp. 823–58, https://doi.org/10.1007/s11004-020-09895-w.
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