simulatiom data with sas/iml

thanoon — Sun, 24 Nov 2013 14:31:20 GMT

HI ALL

i need your help to correct this commands ( simulation of multivariate regression model).

regards\

&let N=1000;

proc iml;

/* specify the mean and covariance of the population */

Mean = {1, 2, 3 , 4, 5, 6, 7, 8, 9};

cov = {0.8838659 0.9738211 0.5075826 0.8869405 0.6893635 0.9432546 0.9287864 0.487664 0.7798851,

0.9738211 0.8771385 0.5668343 0.6656078 0.8234433 0.9280248 0.7900982 0.1142881 0.8905852,

0.5075826 0.5668343 0.5448972 0.2810451 0.9316785 0.6140648 0.8564316 0.6149666 0.4655727,

0.8869405 0.6656078 0.2810451 0.5900954 0.7749225 0.4426628 0.0762391 0.9093871 0.5513743,

0.6893635 0.8234433 0.9316785 0.7749225 0.6663087 0.236998 0.1419535 0.3321644 0.3306588,

0.9432546 0.9280248 0.6140648 0.4426628 0.236998 0.7543832 0.6882105 0.6199138 0.7862424,

0.9287864 0.7900982 0.8564316 0.0762391 0.1419535 0.6882105 0.9863298 0.1584623 0.3849384,

0.487664 0.1142881 0.6149666 0.9093871 0.3321644 0.6199138 0.1584623 0.3205565 0.0744708,

0.7798851 0.8905852 0.4655727 0.5513743 0.3306588 0.7862424 0.3849384 0.0744708 0.4806334}

call randseed(4321);

X = RandNormal(&N, Mean, Cov); /* 1000 x 9 matrix */

/* check the sample mean and sample covariance */

SampleMean = mean(X); /* mean of each column */

SampleCov = cov(X); /* sample covariance */

/* print results */

c = "x1":"x9";

print (X[1000:9,])[label="First 5 Obs: MV Normal"];

print SampleMean[colname=c];

print SampleCov[colname=c rowname=c];

/* write SAS/IML matrix to SAS data set for plotting */

create MVN from X[colname=c]; append from X; close MVN;

quit;

run;

Re: simulatiom data with sas/iml

thanoon — Sun, 24 Nov 2013 15:08:14 GMT

i am sorry i forget the linear equation :

%let N=1000;

proc iml;

/* specify the mean and covariance of the population */

Mean = {1, 2, 3, 2, 1, 4, 5, 6, 1};

Cov = {0.8838659 0.9738211 0.5075826 0.8869405 0.6893635 0.9432546 0.9287864 0.487664 0.7798851,

0.9738211 0.8771385 0.5668343 0.6656078 0.8234433 0.9280248 0.7900982 0.1142881 0.8905852,

0.5075826 0.5668343 0.5448972 0.2810451 0.9316785 0.6140648 0.8564316 0.6149666 0.4655727,

0.8869405 0.6656078 0.2810451 0.5900954 0.7749225 0.4426628 0.0762391 0.9093871 0.5513743,

0.6893635 0.8234433 0.9316785 0.7749225 0.6663087 0.236998 0.1419535 0.3321644 0.3306588,

0.9432546 0.9280248 0.6140648 0.4426628 0.236998 0.7543832 0.6882105 0.6199138 0.7862424,

0.9287864 0.7900982 0.8564316 0.0762391 0.1419535 0.6882105 0.9863298 0.1584623 0.3849384,

0.487664 0.1142881 0.6149666 0.9093871 0.3321644 0.6199138 0.1584623 0.3205565 0.0744708,

0.7798851 0.8905852 0.4655727 0.5513743 0.3306588 0.7862424 0.3849384 0.0744708 0.4806334};

call randseed(4321);

X = RandNormal(&N, Mean, Cov); /* 1000 x 9 matrix */

/* check the sample mean and sample covariance */

SampleMean = mean(X); /* mean of each column */

SampleCov = cov(X); /* sample covariance */

/* generate Y according to regression model */

beta = {2, 1, -1, 2, 1, 5, 6, 2, -2}; /* params, not including intercept */

Y = 1 + X*beta + eps;

/* write SAS data set */

varNames = ('x1':'x9') || {"Y"};

output = X || Y;

run;

topic Re: simulatiom data with sas/iml in SAS/IML Software and Matrix Computations

simulatiom data with sas/iml

Re: simulatiom data with sas/iml