QUICK CLUSTER: Add documentation

[pspp] / doc / statistics.texi

diff --git a/doc/statistics.texi b/doc/statistics.texi
index 599e7e42903bab70945735e8f455232af8230886..36727c44c5f75dfa7620e900029875d4c2dd874b 100644 (file)
--- a/doc/statistics.texi
+++ b/doc/statistics.texi
@@ -14,6 +14,7 @@ far.
 * NPAR TESTS::                  Nonparametric tests.
 * T-TEST::                      Test hypotheses about means.
 * ONEWAY::                      One way analysis of variance.
 * NPAR TESTS::                  Nonparametric tests.
 * T-TEST::                      Test hypotheses about means.
 * ONEWAY::                      One way analysis of variance.

+* QUICK CLUSTER::               K-Means clustering.

 * RANK::                        Compute rank scores.
 * REGRESSION::                  Linear regression.
 * RELIABILITY::                 Reliability analysis.
 * RANK::                        Compute rank scores.
 * REGRESSION::                  Linear regression.
 * RELIABILITY::                 Reliability analysis.


@@ -1169,10 +1170,52 @@ that @var{value} should be used as the
 confidence level for which the posthoc tests will be performed.
 The default is 0.05.
 
 confidence level for which the posthoc tests will be performed.
 The default is 0.05.
 

+@node QUICK CLUSTER
+@comment  node-name,  next,  previous,  up
+@section QUICK CLUSTER
+@vindex QUICK CLUSTER
+
+@cindex K-means clustering
+@cindex clustering
+
+@display
+QUICK CLUSTER var_list
+      [/CRITERIA=CLUSTERS(@var{k}) [MXITER(@var{max_iter})]]
+      [/MISSING=@{EXCLUDE,INCLUDE@} @{LISTWISE, PAIRWISE@}]
+@end display
+
+The @cmd{QUICK CLUSTER} command performs k-means clustering on the
+dataset.  This is useful when you wish to allocate cases into clusters
+of similar values and you already know the number of clusters.
+
+The minimum specification is @samp{QUICK CLUSTER} followed by the names
+of the variables which contain the cluster data.  Normally you will also
+want to specify @samp{/CRITERIA=CLUSTERS(@var{k})} where @var{k} is the
+number of clusters.  If this is not given, then @var{k} defaults to 2.
+
+The command uses an iterative algorithm to determine the clusters for
+each case.  It will continue iterating until convergence, or until @var{max_iter}
+iterations have been done.  The default value of @var{max_iter} is 2.
+
+The @cmd{MISSING} subcommand determines the handling of missing variables.  
+If INCLUDE is set, then user-missing values are considered at their face
+value and not as missing values.
+If EXCLUDE is set, which is the default, user-missing
+values are excluded as well as system-missing values. 
+
+If LISTWISE is set, then the entire case is excluded from the analysis
+whenever any of the clustering variables contains a missing value.   
+If PAIRWISE is set, then a case is considered missing only if all the
+clustering variables contain missing values.  Otherwise it is clustered
+on the basis of the non-missing values.
+The default is LISTWISE.
+
+

 @node RANK
 @comment  node-name,  next,  previous,  up
 @section RANK
 
 @node RANK
 @comment  node-name,  next,  previous,  up
 @section RANK
 

+

 @vindex RANK
 @display
 RANK
 @vindex RANK
 @display
 RANK