PROC MDS <options>;
The PROC MDS statement invokes the MDS procedure. PROC MDS produces an iteration history by default. Graphical displays are produced when ODS Graphics is enabled. Additional displayed output is controlled by the interaction of the PCONFIG, PCOEF, PTRANS, PFIT, and PFITROW options with the PININ, PINIT, PITER, and PFINAL options. The PCONFIG, PCOEF, PTRANS, PFIT, and PFITROW options specify which estimates and fit statistics are to be displayed. The PININ, PINIT, PITER, and PFINAL options specify when the estimates and fit statistics are to be displayed. If you specify at least one of the PCONFIG, PCOEF, PTRANS, PFIT, and PFITROW options but none of the PININ, PINIT, PITER, and PFINAL options, the final results (PFINAL) are displayed. If you specify at least one of the PININ, PINIT, PITER, and PFINAL options but none of the PCONFIG, PCOEF, PTRANS, PFIT, and PFITROW options, all estimates (PCONFIG, PCOEF, PTRANS) and the fit statistics for each matrix and for the entire sample (PFIT) are displayed. If you do not specify any of these nine options, no estimates or fit statistics are displayed (except the badnessoffit criterion in the iteration history).
The types of estimates written to the OUT= data set are determined by the OCONFIG, OCOEF, OTRANS, and OCRIT options. If you do not specify any of these four options, the estimates of all the parameters of the PROC MDS model and the value of the badnessoffit criterion appear in the OUT= data set. If you specify one or more of these options, only the information requested by the specified options appears in the OUT= data set. Also, the OITER option causes these statistics to be written to the OUT= data set after initialization and on each iteration, as well as after the iterations have terminated.
Table 74.1 summarizes the options available in the PROC MDS statement.
Table 74.1: Summary of PROC MDS Statement Options
Option 
Description 

Data Set Options 

Specifies the input SAS data set 

Specifies the input SAS data set containing initial values 

Specifies the output data set 

Specifies the output fit data set 

Specifies the output residual data set 

Input Control 

Replaces data values with missing values 

Specifies the shape of the input data matrices 

Specifies that the data are similarity measurements 

Model 

Specifies the type of matrix for the coefficients 

Specifies the conditionality of the data 

Specifies the number of dimensions 

Specifies the measurement level 

Permits slopes or powers to be negative 

Permits tied data to be untied 

Initialization 

Affects the computation of initial coordinates 

Specifies the missing data initialization 

Specifies initial random coordinates 

Estimation 

Specifies the alternatingleastsquares algorithm 

Specifies the convergence criterion 

Specifies the amount added to squared distances 

Specifies a predetermined transformation 

Specifies the badnessoffit formula 

Specifies the gradient convergence criterion 

Specifies the maximum number of iterations 

Specifies the monotone convergence criterion 

Specifies the minimum badnessoffit criterion 

Suppresses normalization of the initial and final estimates 

Specifies the maximum overrelaxation factor 

Specifies the initial ridge value 

Specifies the singularity criterion 

Control Output Data Set Contents 

Writes the dimension coefficients to the OUT= data set 

Writes the coordinates of the objects to the OUT= data set 

Writes the badnessoffit criterion to the OUT= data set 

Writes current values after initialization and on every iteration 

Writes the transformation parameter estimates to the OUT= data set 

Control Displayed Output 

Specifies how many decimal places to use 

Suppresses the iteration history 

Displays the estimated dimension coefficients 

Displays the estimated coordinates 

Displays each data matrix 

Displays final estimates 

Displays the badnessoffit criterion 

Displays the badnessoffit criterion for each row 

Displays INAV= data set information 

Displays the initial eigenvalues 

Displays the initial eigenvectors 

Displays values read from the INITIAL= data set 

Displays initial values 

Displays estimates on each iteration 

Controls the graphical displays 

Displays the estimated transformation parameters 