Robust regression and outlier detection
Robust regression and outlier detection
Design patterns: elements of reusable object-oriented software
Design patterns: elements of reusable object-oriented software
Scalable robust covariance and correlation estimates for data mining
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Unified Modeling Language User Guide, The (2nd Edition) (Addison-Wesley Object Technology Series)
Unified Modeling Language User Guide, The (2nd Edition) (Addison-Wesley Object Technology Series)
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Data outliers or other data inhomogeneities lead to a violation of the assumptions of traditional statistical estimators and methods. Robust statistics offers tools that can reliably work with contaminated data. Here, outlier detection methods in low and high dimension, as well as important robust estimators and methods for multivariate data are reviewed, and the most important references to the corresponding literature are provided. Algorithms are discussed, and routines in R are provided, allowing for a straightforward application of the robust methods to real data.