The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.
An Object-Oriented Framework for Robust Multivariate Analysis
Open accessAbstract
Taking advantage of the S4 class system of the programming environment R, which facilitates the creation and maintenance of reusable and modular components, an object-oriented framework for robust multivariate analysis was developed. The framework resides in the packages robustbase and rrcov and includes an almost complete set of algorithms for computing robust multivariate location and scatter, various robust methods for principal component analysis as well as robust linear and quadratic discriminant analysis. The design of these methods follows common patterns which we call statistical design patterns in analogy to the design patterns widely used in software engineering. The application of the framework to data analysis as well as possible extensions by the development of new methods is demonstrated on examples which themselves are part of the package rrcov.
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“To take into account the effect of possible outliers, all regressions with the discount rate were robust [using the robustbase package in R (76)].”
From Adolescent impatience decreases with increased frontostriatal connectivity (2015) · cites this paper as [76]
Citations
Cites
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A Fast Algorithm for the Minimum Covariance Determinant Estimator
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A Fast Algorithm for the Minimum Covariance Determinant Estimator
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Sarkar, D. (2008) · Springer eBooks · doi:10.1007/978-0-387-75969-2 · Cited by 1,792
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Cited by
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mclust 5: Clustering, Classification and Density Estimation Using Gaussian Finite Mixture Models
Scrucca, L., Fop, M., Murphy, T. B., & Adrian, E. R. (2016) · The R Journal · doi:10.32614/rj-2016-021 · Cited by 2,914
Graph-based approach for airborne light detection and ranging segmentation
Vilarino, D. L., Cabaleiro, J. C., Sánchez, J. M., Rivera, F. F., & Pena, T. F. (2017) · Journal of Applied Remote Sensing · doi:10.1117/1.jrs.11.015020 · Cited by 1,760
Robust statistical methods in R using the WRS2 package
Mair, P., & Wilcox, R. R. (2019) · Behavior Research Methods · doi:10.3758/s13428-019-01246-w · Cited by 1,089
A Toolbox for Nonlinear Regression in R : The Package nlstools
Baty, F., Ritz, C., Charles, S., Brutsche, M. H., Flandrois, J., & Delignette‐Muller, M. L. (2015) · Journal of Statistical Software · doi:10.18637/jss.v066.i05 · Cited by 718
Studer, M., & Ritschard, G. (2015) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1111/rssa.12125 · Cited by 502
Metadata
- Authors
- Todorov, V., & Filzmoser, P.
- ORCID
- Todorov, Valentin
- Venue
- Journal of Statistical Software
- Publisher
- Foundation for Open Access Statistic
- Published
- 2009
- Volume
- 32
- Issue
- 3
- ISSN
- 1548-7660 (ISSN-L)
- OpenAlex
- W2157324002
- Cited by
- 420
- References
- 54
- Citations by year
- 2026: 27 · 2025: 43 · 2024: 39 · 2023: 28 · 2022: 18 · 2021: 25 · 2020: 39 · 2019: 29 · 2018: 27 · 2017: 20 · 2016: 32 · 2015: 23 · 2014: 22 · 2013: 17 · 2012: 16
- FWCI
- 9.43
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by
- Locations
- Journal of Statistical Software (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Statistical Methods and Models
- Physical Sciences › Mathematics › Statistics and Probability › Data Analysis with R
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Keywords
- object-oriented design, R programming language, S4 classes, robust principal component analysis, robust discriminant analysis
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