dc.contributor.author	Dudley, Prof. Richard
dc.date.accessioned	2014-07-02T14:44:28Z
dc.date.accessioned	2014-07-02T14:45:08Z
dc.date.available	2014-07-02T14:44:28Z
dc.date.available	2014-07-02T14:45:08Z
dc.date.issued	2003
dc.description	This graduate-level course focuses on one-dimensional nonparametric statistics developed mainly from around 1945 and deals with order statistics and ranks, allowing very general distributions. For multidimensional nonparametric statistics, an early approach was to choose a fixed coordinate system and work with order statistics and ranks in each coordinate. A more modern method, to be followed in this course, is to look for rotationally or affine invariant procedures. These can be based on empirical processes as in computer learning theory. Robustness, which developed mainly from around 1964, provides methods that are resistant to errors or outliers in the data, which can be arbitrarily large. Nonparametric methods tend to be robust.	en_US
dc.identifier.uri	http://hdl.handle.net/123456789/148
dc.publisher	MIT Course Number	en_US
dc.title	Topics in Statistics Nonparametrics and Robustness (PDF )	en_US

Topics in Statistics Nonparametrics and Robustness (PDF )

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