+@node MATRIX DATA
+@section MATRIX DATA
+@vindex MATRIX DATA
+
+@display
+MATRIX DATA
+ VARIABLES = @var{columns}
+ [FILE='@var{file_name}'| INLINE @}
+ [/FORMAT= [@{LIST | FREE@}]
+ [@{UPPER | LOWER | FULL@}]
+ [@{DIAGONAL | NODIAGONAL@}]]
+ [/N= @var{n}]
+ [/SPLIT= @var{split_variables}].
+@end display
+
+The @cmd{MATRIX DATA} command is used to input data in the form of matrices
+which can subsequently be used by other commands. If the
+@subcmd{FILE} is omitted or takes the value @samp{INLINE} then the command
+should immediately followed by @cmd{BEGIN DATA}, @xref{BEGIN DATA}.
+
+There is one mandatory subcommand, @i{viz:} @subcmd{VARIABLES}, which defines
+the @var{columns} of the matrix.
+Normally, the @var{columns} should include an item called @samp{ROWTYPE_}.
+The @samp{ROWTYPE_} column is used to specify the purpose of a row in the
+matrix.
+
+@example
+matrix data
+ variables = rowtype_ var01 TO var08.
+
+begin data.
+mean 24.3 5.4 69.7 20.1 13.4 2.7 27.9 3.7
+sd 5.7 1.5 23.5 5.8 2.8 4.5 5.4 1.5
+n 92 92 92 92 92 92 92 92
+corr 1.00
+corr .18 1.00
+corr -.22 -.17 1.00
+corr .36 .31 -.14 1.00
+corr .27 .16 -.12 .22 1.00
+corr .33 .15 -.17 .24 .21 1.00
+corr .50 .29 -.20 .32 .12 .38 1.00
+corr .17 .29 -.05 .20 .27 .20 .04 1.00
+end data.
+@end example
+
+In the above example, the first three rows have ROWTYPE_ values of
+@samp{mean}, @samp{sd}, and @samp{n}. These indicate that the rows
+contain mean values, standard deviations and counts, respectively.
+All subsequent rows have a ROWTYPE_ of @samp{corr} which indicates
+that the values are correlation coefficients.
+
+Note that in this example, the upper right values of the @samp{corr}
+values are blank, and in each case, the rightmost value is unity.
+This is because, the
+@subcmd{FORMAT} subcommand defaults to @samp{LOWER DIAGONAL},
+which indicates that only the lower triangle is provided in the data.
+The opposite triangle is automatically inferred. One could instead
+specify the upper triangle as follows:
+
+
+@example
+matrix data
+ variables = rowtype_ var01 TO var08
+ /format = upper nodiagonal.
+
+begin data.
+mean 24.3 5.4 69.7 20.1 13.4 2.7 27.9 3.7
+sd 5.7 1.5 23.5 5.8 2.8 4.5 5.4 1.5
+n 92 92 92 92 92 92 92 92
+corr .17 .50 -.33 .27 .36 -.22 .18
+corr .29 .29 -.20 .32 .12 .38
+corr .05 .20 -.15 .16 .21
+corr .20 .32 -.17 .12
+corr .27 .12 -.24
+corr -.20 -.38
+corr .04
+end data.
+@end example
+
+In this example the @samp{NODIAGONAL} keyword is used. Accordingly
+the diagonal values of the matrix are omitted. This implies that
+there is one less @samp{corr} line than there are variables.
+If the @samp{FULL} option is passed to the @subcmd{FORMAT} subcommand,
+then all the matrix elements must be provided, including the diagonal
+elements.
+
+In the preceding examples, each matrix row has been specified on a
+single line. If you pass the keyword @var{FREE} to @subcmd{FORMAT}
+then the data may be data for several matrix rows may be specified on
+the same line, or a single row may be split across lines.
+
+The @subcmd{N} subcommand may be used to specify the number
+of valid cases for each variable. It should not be used if the
+data contains a record whose ROWTYPE_ column is @samp{N} or @samp{N_VECTOR}.
+It implies a @samp{N} record whose values are all @var{n}.
+That is to say,
+@example
+matrix data
+ variables = rowtype_ var01 TO var04
+ /format = upper nodiagonal
+ /n = 99.
+begin data
+mean 34 35 36 37
+sd 22 11 55 66
+corr 9 8 7
+corr 6 5
+corr 4
+end data.
+@end example
+produces an effect identical to
+@example
+matrix data
+ variables = rowtype_ var01 TO var04
+ /format = upper nodiagonal
+begin data
+n 99 99 99 99
+mean 34 35 36 37
+sd 22 11 55 66
+corr 9 8 7
+corr 6 5
+corr 4
+end data.
+@end example
+
+
+The @subcmd{SPLIT} is used to indicate that variables are to be
+considered as split variables. For example, the following
+defines two matrices using the variable @samp{S1} to distinguish
+between them.
+
+@example
+matrix data
+ variables = s1 rowtype_ var01 TO var04
+ /split = s1
+ /format = full diagonal.
+
+begin data
+0 mean 34 35 36 37
+0 sd 22 11 55 66
+0 n 99 98 99 92
+0 corr 1 9 8 7
+0 corr 9 1 6 5
+0 corr 8 6 1 4
+0 corr 7 5 4 1
+1 mean 44 45 34 39
+1 sd 23 15 51 46
+1 n 98 34 87 23
+1 corr 1 2 3 4
+1 corr 2 1 5 6
+1 corr 3 5 1 7
+1 corr 4 6 7 1
+end data.
+@end example
+
projects / pspp / blobdiff