Dataplot Vol 2 Vol 1

# GENERATE MATRIX

Name:
GENERATE MATRIX (LET)
Type:
Let Subcommand
Purpose:
Given a list of k variables, generate a kxk matrix containing all the pairwise values of a specified statistic that requires exactly two response variables.
Description:
This command can be useful for certain types of multivariate analysis. For example, it can be used to generate a dissimilarity or distance matrix for a cluster analysis.

The specified statistic should require exactly two response variables to compute. Examples include correlation and covariances, various distance measures, differences of location or scale statistics, and so on. Statistics that require a single response variable or more than two response variables will return an error.

A number of supported statistics that require two response variables have the second variable as a group-id variable. Although this command will not generate a syntax error for these cases, the resulting statistics will not be meaningful.

Syntax:
LET <mat1> = GENERATE MATRIX <stat> <var1> ... <vark>
<SUBSET/EXCEPT/FOR qualification>
where <stat> is one of Dataplot's supported statistics that requires exactly two response variable;
<var1> ... <vark> is a list of previously defined variables;
<mat1> is a matrix where the resulting matrix is saved;
and where the <SUBSET/EXCEPT/FOR qualification> is optional.
Examples:
LET C = GENERATE MATRIX CORRELATION X1 X2 X3 X4
LET D = GENERATE MATRIX MANHATTAN DISTANCE Y1 Y2 Y3 Y4 Y5
Note:
The columns of a matrix are accessible as variables by appending an index to the matrix name. For example, the 4x4 matrix C has columns C1, C2, C3, and C4. These columns can be operated on like any other Dataplot variable.
Note:
For a list of supported statistics, enter

Default:
None
Synonyms:
None
Related Commands:
 CREATE MATRIX = Create a matrix from a list of variables. CORRELATION MATRIX = Create a correlation matrix from a matrix of response variables. STATISTIC = Provides a list of supported statistics.
Applications:
Multivariate Analyis
Implementation Date:
2017/08
Program:

set write decimals 3
dimension 100 columns
.
skip 25
read iris.dat y1 y2 y3 y4
skip 0
.
. Step 2:   Generate the matrix
.
let m = generate matrix correlation y1 y2 y3 y4
print m
.
let m = generate matrix euclidean distance y1 y2 y3 y4
print m
.
let m = generate matrix difference of means y1 y2 y3 y4
print m

The following output is generated
        MATRIX CORR    --            4 ROWS
--            4 COLUMNS

VARIABLES--CORR1          CORR2          CORR3          CORR4

1.000         -0.118          0.850          0.691
-0.118          1.000         -0.472         -0.068
0.850         -0.472          1.000          0.712
0.691         -0.068          0.712          1.000

MATRIX D       --            4 ROWS
--            4 COLUMNS

VARIABLES--D1             D2             D3             D4

0.000         36.158         35.262         61.489
36.158          0.000         30.185         29.383
35.262         30.185          0.000         37.665
61.489         29.383         37.665          0.000

MATRIX DIFF    --            4 ROWS
--            4 COLUMNS

VARIABLES--DIFF1          DIFF2          DIFF3          DIFF4

0.000          2.786          2.419          4.977
-2.786          0.000         -0.367          2.191
-2.419          0.367          0.000          2.559
-4.977         -2.191         -2.559          0.000


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Date created: 08/31/2017
Last updated: 08/31/2017