Robust Statistics

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Here’s a video I put together as part of a job application process discussing the concept of robustness and highlighting the aim of robust estimators.

The slides are here: http://garthtarr.com/pres/RobIntro

Note that you may need to refresh the slides to get the network graphs to appear.

References:

Location: Hodges-Lehmann estimator
http://en.wikipedia.org/wiki/Hodges-Lehmann_estimator
Hodges, Lehmann (1963). Estimation of location based on ranks. Annals of Mathematical Statistics 34(2): 598-611. DOI: 10.1214/aoms/1177704172

Covariance: Minimum Covariance Determinant (MCD) estimator
Hubert, Debruyne (2010). Minimum covariance determinant. Wiley Interdisciplinary Reviews: Computational Statistics, 2: 36-43. DOI: 10.1002/wics.61

Sparse precision matrix estimation: Graphical lasso
Friedman, Hastie, Tibshirani (2008). Sparse inverse covariance estimation with the graphical lasso. Biostatistics, 9(3): 432-441. DOI: 10.1093/biostatistics/kxm045

Robust precision matrix estimation
Tarr, Müller, Weber (2015). Robust estimation of precision matrices under cellwise contamination. Computational Statistics & Data Analysis, to appear. DOI: 10.1016/j.csda.2015.02.005

Robust scale estimation
Tarr, Müller, Weber (2012). A robust scale estimator based on pairwise means. Journal of Nonparametric Statistics, 24(1): 187-199. DOI: 10.1080/10485252.2011.621424

Overview of robust estimation of scale and dependence
Tarr, (2014). Quantile Based Estimation of Scale and Dependence. PhD Thesis. University of Sydney, Australia. hdl.handle.net/2123/10590

By | 2016-10-15T05:47:43+00:00 March 5th, 2015|Statistics|0 Comments

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