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From: saswss@hotellng.unx.sas.com (Warren Sarle)
Subject: Re: How to classify with only 1 class?
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Date: Sat, 4 May 1996 18:54:03 GMT
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In article <4m3l7k$9hk@llnews.ll.mit.edu>, heath@ll.mit.edu (Greg Heath) writes:
|> |> ...
|> |> As stated, I don't think that there is a proper direct answer. However, 
|> |> I think the following null hypothesis, H0, can either be accepted with 
|> |> a certain level of confidence, C%, or rejected at a certain level of 
|> |> significance, a% (C% + a% = 100%), with respect to the following 
|> |> alternative hypothesis, H1: 
|> |> 
|> |> H0: The measurement x = X comes from a normal distribution with 
|> |>     estimated mean and standard deviation (m,s).  
|> |> H1: The measurement x = X does not come from a normal distribution 
|> |>     with estimated mean and standard deviation (m,s).
|> |> ...
|> Generalization to a 1-D nonsymmetric distribution will be attempted in a 
|> following post.

Any 1-D distribution is straightforward. Even if you can't integrate
the density analytically, you can integrate it numerically. The problem
is how to do the integration in high dimensions for anything other
than a very tractable distribution like a multivariate normal.

-- 

Warren S. Sarle       SAS Institute Inc.   The opinions expressed here
saswss@unx.sas.com    SAS Campus Drive     are mine and not necessarily
(919) 677-8000        Cary, NC 27513, USA  those of SAS Institute.
