Comparison with the MLSCALE Procedure

The MDS Procedure

Comparison with the MLSCALE Procedure

Running the MDS procedure with the options

   proc mds fit=log level=loginterval ... ;

generally produces results similar to using the MLSCALE procedure (Ramsay 1986) with the options

   proc mlscale stvarnce=constant suvarnce=constant ... ;

Alternatively, using the FIT=DISTANCE option in the PROC MDS statement produces results similar to specifying the NORMAL option in the PROC MLSCALE statement.

The MDS procedure uses the least-squares method of estimation. The least-squares method is equivalent to the maximum-likelihood method if the error terms are assumed to be independent and identically distributed normal random variables. Unlike PROC MLSCALE, PROC MDS does not provide any options for unequal error variances.

PROC MDS accepts some PROC MLSCALE options as synonyms for the options described previously, as displayed in Table 40.2.

Table 40.2: PROC MDS Options Compared to PROC MLSCALE Options

	Accepted by	Related PROC MDS Option
PROC MLSCALE Option	PROC MDS?	or Comments
SQUARE	Yes	SHAPE=SQUARE
INPUT=MATRIX	No	Default
INPUT=VECTOR	No
STLABEL=	No	ID statement
STLBDS	No
SULABEL=	No	MATRIX statement
SULBDS	No
CONFIG	No
CONFDS=	No	IN= data set
NEQU=	No
CONSDS=	No
METVAL	No
METVDS	No	IN=
SEWGTS	No
SEWGDS=	No
SPLVAL	No
SLPVDS=	No
DIMENS=	Yes
METRIC=IDENTITY	Yes	COEF=IDENTITY
METRIC=DIAGONAL	Yes	COEF=DIAGONAL
METRIC=FULL	No
TRANSFRM=SCALE	Yes	LEVEL=RATIO
TRANSFRM=POWER	Yes	LEVEL=LOGINTERVAL
TRANSFRM=SPLINE	No
STVARNCE=	No
SUVARNCE=	No
NORMAL	No	Default (FIT=DISTANCE)
ITMAX=	Yes	MAXITER=
ITXMAX=	No
ITWMAX=	No
ITAMAX=	No
ITPMAX=	No
CONV=	(Yes)	Meaning is different
FACTOR=	No
HISTORY	No	PITER
ASYMP	No
OUTCON	No	OUT=
OUTDIS	No
OUTMET	No	OUT=
OUTSPL	No
OUTRES	(Yes)	OUTRES= data set

Chapter Contents
Previous
Next
Top