John wrote:
Hello,
I've been searching for a method for identify outliers for quite some
time now. The complication is that I cannot assume that my data is
normally distributed nor symmetrical (i.e. some distributions might
have one longer tail) so I have not been able to find any good tests.
The Walsh's Test (http://www.statistics4u.info/
fundsta...liertest.html#), as I understand assumes that the data is
symmetrical for example.
Also, while I've found some interesting articles:
http://tinyurl.com/yc7w4oq ("Missing Values, Outliers, Robust
Statistics & Non-parametric Methods")
I don't really know what to use.
Any ideas? Any R packages available for this? Thanks!
PS. My data has 1000's of observations..
Take a look at package 'robustbase', it provides most of the standard robust
measures and calculations.
While you didn't say what kind of data you're trying to identify outliers in,
if it is time series data the function Return.clean in PerformanceAnalytics may
be useful.
Regards,
- Brian
--
Brian G. Peterson
http://braverock.com/brian/
Ph: 773-459-4973
IM: bgpbraverock
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