Help with Distribution-Free Outlier Test | jophysics

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A user is seeking assistance with finding a distribution-free outlier test. Walsh's outlier test is suggested as a potential solution. The discussion remains focused on identifying effective methods for outlier detection without relying on specific distribution assumptions. Further contributions may provide additional options or insights into the topic. The conversation emphasizes the need for robust statistical methods in outlier analysis.
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Hi all,
I am searching a distribution-free outliers test. Someone can help me?

thank you


jophysics
 
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Have you looked at Walsh's outlier test?
 

Thread 'Hypothesis testing: Defining H0, HA hypotheses so that ( H_A)_A' makes sense'

The standard _A " operator" maps a Null Hypothesis Ho into a decision set { Do not reject:=1 and reject :=0}. In this sense ( HA)_A , makes no sense. Since H0, HA aren't exhaustive, can we find an alternative operator, _A' , so that ( H_A)_A' makes sense? Isn't Pearson Neyman related to this? Hope I'm making sense. Edit: I was motivated by a superficial similarity of the idea with double transposition of matrices M, with ## (M^{T})^{T}=M##, and just wanted to see if it made sense to talk...
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