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help for ^distan^
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Calculates similarity and dissimilarity measures
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	^distan^ varlist^, st^andar ^di^stan^(^distance-measure^)^ ^av^erage
^sa^ve^(^filename^)^


Description
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^distan^ calculates similarity and dissimilarity measures between
observations


Options
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^st^andar standarizes the variables in ^varlist^.

^di^stan^(^distance-measure^)^. Euclidian distance is used as default.
The following
measures are allowed:

	^co^variance: covariance between observations.

	^cor^relation: correlation coefficient between observations.

	^ma^nhattan: Manhattan distance between observations.

	^mi^nkowski^[^n^]^: Minkowski metrics of dimension ^n^. Euclidian and
	Manhattan distances are particular cases of dimension 2 and 1 
	respectively.

^average^ calculates mean distances if Manhattan, Euclidian or Minkowski
distances are specified. This option is specially useful if missing
values
are present in the original dataset.

^sa^ve^(^filename^)^ saves the results to ^filename^


Remarks
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Saved output contains three variables: ^elem1^, ^elem2^ and ^distan^.
The first two
identify the observation numbers of the original dataset for which the
distance
^distan^ was calculated.


Examples
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 . ^distan x y z, st^
 . ^distan x y z, di(mi[3.2]) av sa(c:\dist.dta)^
 . ^distan x y z, di(cor)^


Author
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Jose Maria Sanchez Saez
