Dr. Wicklin's text provides significant support for simulating data from correlated multivariate distributions. However, his text does not provide code for Simulating data from Correlated Multivariate Uniform Distributions. Can anyone provide some example code? For example, could I simply change the RANNOR to RANUNI in the below code? data MVN (type = CORR); _TYPE_='CORR'; set bhf.R; run; proc factor N=19 OUTSTAT=FACOUT; run; DATA PATTERN; SET FACOUT; IF _TYPE_='PATTERN'; DROP _TYPE_ _NAME_; RUN; PROC IML; USE PATTERN; READ ALL VAR _NUM_ INTO F; F=F`; PRINT f; DATA = RANNOR(J(10000,19,0)); DATA = DATA`; Z = F*DATA; Z = Z`; X1=Z[,1]*0.418378 + 0.01284361; X2=Z[,2]*0.418378 + 0.06569127; X3=Z[,3]*0.418378 + 0.02904674; X4=Z[,4]*0.418378 + 0.01284361; X5=Z[,5]*0.418378 + 0.02904674; X6=Z[,6]*0.418378 + 0.09878997; X7=Z[,7]*0.418378 + 0.02904674; X8=Z[,8]*0.418378 + 0.043682; X9=Z[,9]*0.418378 + 0.06569127; X10=Z[,10]*0.418378 + 0.043682; X11=Z[,11]*0.418378 + 0.01931489; X12=Z[,12]*0.418378 + 0.02904674; X13=Z[,13]*0.418378 + 0.02904674; X14=Z[,14]*0.418378 + 0.0437; X15=Z[,15]*0.418378 + 0.0657; X16=Z[,16]*0.418378 + 0.02904674; X17=Z[,17]*0.418378 + 0.043682; X18=Z[,18]*0.418378 + 0.01931489; X19=Z[,19]*0.418378 + 0.02904674; Z=X1||X2||X3||X4||X5||X6||X7||X8||X9||X10||X11||X12 ||X13||X14||X15||X16||X17||X18||X19; CREATE A FROM Z [COLNAME={X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 X14 X15 X16 X17 X18 X19}]; APPEND FROM Z; PROC MEANS DATA=A N MEAN STD SKEWNESS KURTOSIS; VAR X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 X14 X15 X16 X17 X18 X19; PROC CORR DATA=A NOSIMPLE; VAR X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 X14 X15 X16 X17 X18 X19; RUN; Thanks!
... View more