X-Git-Url: https://pintos-os.org/cgi-bin/gitweb.cgi?a=blobdiff_plain;f=doc%2Fstatistics.texi;h=522ef4d3100a2132ec5752da4b180eac7a36a82a;hb=d573464ad00fdb72c27e3c36d8f862ef99249431;hp=259c9abe53e1626449f251668d25258394879724;hpb=0b7e8882ce9bf2166c6bcc0db1334357ba5a76d4;p=pspp

diff --git a/doc/statistics.texi b/doc/statistics.texi
index 259c9abe53..522ef4d310 100644
--- a/doc/statistics.texi
+++ b/doc/statistics.texi
@@ -1097,7 +1097,7 @@ MEANS [TABLES =]
         [ALL]
         [NONE] ]
 
-      [/MISSING = [TABLE] [INCLUDE] [DEPENDENT]]
+      [/MISSING = [INCLUDE] [DEPENDENT]]
 @end display 
 
 You can use the @cmd{MEANS} command to calculate the arithmetic mean and similar
@@ -1201,10 +1201,6 @@ encountered.
 This behaviour can be modified with the  @subcmd{/MISSING} subcommand.
 Three options are possible: @subcmd{TABLE}, @subcmd{INCLUDE} and @subcmd{DEPENDENT}.
 
-@subcmd{/MISSING = TABLE} causes cases to be dropped if any variable is missing 
-in the table specification currently being processed, regardless of 
-whether it is needed to calculate the statistic.
-
 @subcmd{/MISSING = INCLUDE} says that user missing values, either in the dependent
 variables or in the categorical variables should be taken at their face
 value, and not excluded.
@@ -1819,6 +1815,7 @@ QUICK CLUSTER @var{var_list}
       [/CRITERIA=CLUSTERS(@var{k}) [MXITER(@var{max_iter})] CONVERGE(@var{epsilon}) [NOINITIAL]]
       [/MISSING=@{EXCLUDE,INCLUDE@} @{LISTWISE, PAIRWISE@}]
       [/PRINT=@{INITIAL@} @{CLUSTER@}]
+      [/SAVE[=[CLUSTER[(@var{membership_var})]] [DISTANCE[(@var{distance_var})]]]
 @end display
 
 The @cmd{QUICK CLUSTER} command performs k-means clustering on the
@@ -1871,6 +1868,13 @@ be printed.
 If @subcmd{CLUSTER} is set, the cluster memberships of the individual
 cases will be displayed (potentially generating lengthy output).
 
+You can specify the subcommand @subcmd{SAVE} to ask that each case's cluster membership
+and the euclidean distance between the case and its cluster center be saved to
+a new variable in the active dataset.   To save the cluster membership use the
+@subcmd{CLUSTER} keyword and to save the distance use the @subcmd{DISTANCE} keyword.
+Each keyword may optionally be followed by a variable name in parentheses to specify
+the new variable which is to contain the saved parameter.  If no variable name is specified,
+then PSPP will create one.
 
 @node RANK
 @section RANK