CerioliOutlierDetection | R Documentation |
Implements the outlier detection methodology of Cerioli (2010) based on Mahalanobis distances and the minimum covariance determinant (MCD) estimate of dispersion. Also provides critical values for testing outlyingness of MCD-based Mahalanobis distances using the distribution approximations developed by Hardin and Rocke (2005), Chapter 2 of Green (2017), and Green and Martin (2017).
The function cerioli2010.irmcd.test()
provides the outlier detection
methodology of Cerioli (2010), and is probably the best place for a new user
of this package to start. See the documentation for that function for examples.
This package was also used to produce the results presented in Chapter 2 of Green (2017)
and Green and Martin (2017). There is a companion R
package, HardinRockeExtension
,
that provides code that can be used to replicate the results of that paper. The
package HardinRockeExtension
is available from Christopher G. Green's
GitHub: https://github.com/christopherggreen/HardinRockeExtensionSimulations .
Written and maintained by Christopher G. Green <christopher.g.green@gmail.com>, with advice and support from Doug Martin.
Andrea Cerioli. Multivariate outlier detection with high-breakdown estimators. Journal of the American Statistical Association, 105(489):147-156, 2010. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1198/jasa.2009.tm09147")}
C. G. Green. Applications of Robust Statistical Methods in Quantitative Finance. Dissertation, 2017. Available from https://digital.lib.washington.edu/researchworks/handle/1773/40304
C. G. Green and R. Douglas Martin. An extension of a method of Hardin and Rocke, with an application to multivariate outlier detection via the IRMCD method of Cerioli. Working Paper, 2017. Available from https://christopherggreen.github.io/papers/hr05_extension.pdf
J. Hardin and D. M. Rocke. The distribution of robust distances. Journal of Computational and Graphical Statistics, 14:928-946, 2005. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1198/106186005X77685")}
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