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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
SQUAREYesSHAPE=SQUARE
INPUT=MATRIXNoDefault
INPUT=VECTORNo 
STLABEL=NoID statement
STLBDSNo 
SULABEL=NoMATRIX statement
SULBDSNo 
CONFIGNo 
CONFDS=NoIN= data set
NEQU=No 
CONSDS=No 
METVALNo 
METVDSNoIN=
SEWGTSNo 
SEWGDS=No 
SPLVALNo 
SLPVDS=No 
DIMENS=Yes 
METRIC=IDENTITYYesCOEF=IDENTITY
METRIC=DIAGONALYesCOEF=DIAGONAL
METRIC=FULLNo 
TRANSFRM=SCALEYesLEVEL=RATIO
TRANSFRM=POWERYesLEVEL=LOGINTERVAL
TRANSFRM=SPLINENo 
STVARNCE=No 
SUVARNCE=No 
NORMALNoDefault (FIT=DISTANCE)
ITMAX=YesMAXITER=
ITXMAX=No 
ITWMAX=No 
ITAMAX=No 
ITPMAX=No 
CONV=(Yes)Meaning is different
FACTOR=No 
HISTORYNoPITER
ASYMPNo 
OUTCONNoOUT=
OUTDISNo 
OUTMETNoOUT=
OUTSPLNo 
OUTRES(Yes)OUTRES= data set

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