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Multivariate Transformations

3 messages · Holger Steinmetz, stephen sefick, Gavin Simpson

Original
Holger Steinmetz
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Hello folks,

many multivariate anayses (e.g., structural equation modeling) require
multivariate normal distributions.
Real data, however, most often significantly depart from the multinormal
distribution. Some researchers (e.g., Yuan et al., 2000) have proposed a
multivariate transformation of the variables.

Can you tell me, if and how such a transformation can be handeled in R?

Thanks in advance.
With best regards
Holger


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Yuan, K.-H., Chan, W., & Bentler, P. M. (2000). Robust transformation with
applications to structural equation modeling. British Journal of
Mathematical and Statistical Psychology, 53, 31?50.
stephen sefick
# 
It depends on what you are after.  I am by no means a wunderkind when
it comes to transformation, but in the package vegan type
?wisconsin
and that should give you a start,  but if you know what
transformations you would like to preform then apply should do what
you need with whatever transformation you are trying to use.

Stephen Sefick
On Wed, May 27, 2009 at 5:26 AM, Hollix <Holger.steinmetz at web.de> wrote:

  
    

      
      
    

  


  


      

    

    

      
      

        


  

        

      Gavin Simpson
    

    

      
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On Wed, 2009-05-27 at 08:39 -0400, stephen sefick wrote:

            

      
      
      
    

        
decostand provides (mostly) standardisations not transformations, it
even says so. What Holger is looking for is something like a Box Cox
transform for bivariate normality but to instead achieve multivariate
normality. That is a different kettle of fish to what decostand tries to
do.

HTH

G