topic Re: simulation multivariate ordinal data with 10 variables in SAS/IML Software and Matrix Computations

simulation multivariate ordinal data with 10 variables

thanoon — Thu, 02 Jan 2014 16:33:23 GMT

hi everyone

i have a problem with simulation using sas/iml and i cannot get on data just x1-x10 without data anyone help me please to correct this program.

thanks alot

%include "RandMVOrd.sas";

proc iml;

load module=_all_; /* load the modules */

/* P1 P2 P3 p4 p5 p6 p7 p8 p9 p10 */

P = {0.35 0.50 0.20 0.10 0.10 0.30 0.20 0.25 0.15 0.20,

0.30 0.10 0.20 0.30 0.20 0.20 0.40 0.05 0.45 0.10,

0.15 0.20 0.35 0.25 0.50 0.20 0.25 0.55 0.10 0.10,

0.20 0.20 0.25 0.35 0.20 0.30 0.15 0.15 0.30 0.60};

/* expected values and variance for each ordinal variable */

Expected = Mean(P) // Var(P);

varNames = "X1":"X10";

print Expected[r={"Mean" "Var"} c=varNames];

/* test the RandMVOrd function */

Delta = {1 0.45 0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05,

0.45 1 0.45 0.4 0.35 0.3 0.25 0.2 0.15 0.1,

0.4 0.45 1 0.45 0.4 0.35 0.3 0.25 0.2 0.15,

0.35 0.4 0.45 1 0.45 0.4 0.35 0.3 0.25 0.2,

0.3 0.35 0.4 0.45 1 0.45 0.4 0.35 0.3 0.25,

0.25 0.3 0.35 0.4 0.45 1 0.45 0.4 0.35 0.3,

0.2 0.25 0.3 0.35 0.4 0.45 1 0.45 0.4 0.35,

0.15 0.2 0.25 0.3 0.35 0.4 0.45 1 0.45 0.4,

0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 1 0.45,

0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 1};

call randseed(54321);

X = RandMVOrdinal(1000, P, Delta);

/* print results */

varNames = ('x1':'x10');

create MVO var {X1 X2 X3 X4 X5 X6 X7 X8 X9 X10}; append from var; close MVO; /* write data */

run;

Re: simulation multivariate ordinal data with 10 variables

thanoon — Sun, 05 Jan 2014 08:39:53 GMT

I am waiting anyone help me to correct the previous program please.

Regards

Re: simulation multivariate ordinal data with 10 variables

Rick_SAS — Wed, 08 Jan 2014 16:38:01 GMT

As I commented in another thread (https://communities.sas.com/thread/52019), it is extremely hard to invent means and covariances that are valid. Try using smaller correlations. The following program works:

d = 1 || do(0.4, 0.04, -0.04);
Delta = toeplitz(d);

v = {0.05 0.05 0.05 0.05 0.10 0.10 0.10 0.10 0.2 0.20}`;
P = j(10,10);
P[,1] = v;
call randseed(1);
do i = 2 to 10;
P[,i] = v[ranperm(10)];
end;
print P, Delta;
X = RandMVOrdinal(1000, P, Delta);

Re: simulation multivariate ordinal data with 10 variables

thanoon — Fri, 10 Jan 2014 00:22:31 GMT

thank you so much for your help i dont have any problem when i used small number of variables but in my research i need to simulate at least 10 variables so i forgot to put quotation marks in include statement after that i got on a results. thanks alot

Re: simulation multivariate ordinal data with 10 variables

thanoon — Sat, 25 Jan 2014 12:59:27 GMT

when i simulating data i found some outliers but i dont write any condition to put outliers in data how can i solve this problem.

thanks in advance

Re: simulation multivariate ordinal data with 10 variables

Rick_SAS — Mon, 27 Jan 2014 14:06:22 GMT

If by "outlier" you mean "an observation from an area in which the probability density is low," then this isn't necessarily a problem. You expect to get a few points in those regions. For example, if you simulate 1 million observations from a univariate standard normal distribution, you should expect to get 63 observations such that |x|>4:

P = 2*1e6*Cdf("Normal", -4);

print P;

They are outliers, yes, but they are supposed to be there. The same is true for other distributions. It is only a "problem" if you are observing these low-probability regions more often than theory predicts.

Re: simulation multivariate ordinal data with 10 variables

thanoon — Sun, 16 Feb 2014 14:28:23 GMT

THANKS ALOT

Re: simulation multivariate ordinal data with 10 variables

thanoon — Wed, 19 Feb 2014 13:26:38 GMT

if i want to simulate multi sample data can i just change the rand seed for each one.

thanks in advance

Re: simulation multivariate ordinal data with 10 variables

Rick_SAS — Wed, 19 Feb 2014 14:35:38 GMT

If you want to generate many samples in one program, you can use a loop or just generate one long matrix:

/* loop approach */

NumSamples = 10;

call randseed(54321);

do i = 1 to NumSamples;

X = RandMVOrdinal(1000, P, Delta);

/* do something with each sample */

end;

/* or */

/* each block of 1000 is a sample */

X = RandMVOrdinal(NumSamples*1000, P, Delta);

Re: simulation multivariate ordinal data with 10 variables

thanoon — Wed, 19 Feb 2014 15:07:44 GMT

thanks dr. rick

i want to simulate different samples like different cultures or different countries.

thanks alot

Re: simulation multivariate ordinal data with 10 variables

thanoon — Wed, 19 Feb 2014 15:23:35 GMT

this code is ok now ?

proc iml;

load module=_all_; /* load the modules */

/* P1 P2 P3 p4 p5 p6 p7 p8 p9 p10 */

P = {0.35 0.50 0.20 0.10 0.10 0.30 0.20 0.25 0.15 0.20,

0.30 0.10 0.20 0.30 0.20 0.20 0.40 0.05 0.45 0.10,

0.15 0.20 0.35 0.25 0.50 0.20 0.25 0.55 0.10 0.10,

0.20 0.20 0.25 0.35 0.20 0.30 0.15 0.15 0.30 0.60};

/* expected values and variance for each ordinal variable */

Expected = Mean(P) // Var(P);

varNames = "X1":"X10";

print Expected[r={"Mean" "Var"} c=varNames];

/* test the RandMVOrd function */

Delta = {1 0.45 0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05,

0.45 1 0.45 0.4 0.35 0.3 0.25 0.2 0.15 0.1,

0.4 0.45 1 0.45 0.4 0.35 0.3 0.25 0.2 0.15,

0.35 0.4 0.45 1 0.45 0.4 0.35 0.3 0.25 0.2,

0.3 0.35 0.4 0.45 1 0.45 0.4 0.35 0.3 0.25,

0.25 0.3 0.35 0.4 0.45 1 0.45 0.4 0.35 0.3,

0.2 0.25 0.3 0.35 0.4 0.45 1 0.45 0.4 0.35,

0.15 0.2 0.25 0.3 0.35 0.4 0.45 1 0.45 0.4,

0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 1 0.45,

0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 1};

/* loop approach */

NumSamples = 10;

call randseed(54321);

do i = 1 to NumSamples;

X = RandMVOrdinal(1000, P, Delta);

/* do something with each sample */

/* print results */

c=varNames;

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

quit;

because i receive this warning

WARNING: DO group statements were not executed due to missing END at the time of QUIT.

Re: simulation multivariate ordinal data with 10 variables

thanoon — Sat, 22 Feb 2014 15:51:32 GMT

dear dr.

i still have some errors after putting the previous code can you correct it to me please

proc iml;

load module=_all_; /* load the modules */

/* P1 P2 P3 p4 p5 p6 p7 p8 p9 p10 */

P = {0.35 0.50 0.20 0.10 0.10 0.30 0.20 0.25 0.15 0.20,

0.30 0.10 0.20 0.30 0.20 0.20 0.40 0.05 0.45 0.10,

0.15 0.20 0.35 0.25 0.50 0.20 0.25 0.55 0.10 0.10,

0.20 0.20 0.25 0.35 0.20 0.30 0.15 0.15 0.30 0.60};

/* expected values and variance for each ordinal variable */

Expected = Mean(P) // Var(P);

varNames = "X1":"X10";

print Expected[r={"Mean" "Var"} c=varNames];

/* test the RandMVOrd function */

Delta = {1 0.45 0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05,

0.45 1 0.45 0.4 0.35 0.3 0.25 0.2 0.15 0.1,

0.4 0.45 1 0.45 0.4 0.35 0.3 0.25 0.2 0.15,

0.35 0.4 0.45 1 0.45 0.4 0.35 0.3 0.25 0.2,

0.3 0.35 0.4 0.45 1 0.45 0.4 0.35 0.3 0.25,

0.25 0.3 0.35 0.4 0.45 1 0.45 0.4 0.35 0.3,

0.2 0.25 0.3 0.35 0.4 0.45 1 0.45 0.4 0.35,

0.15 0.2 0.25 0.3 0.35 0.4 0.45 1 0.45 0.4,

0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 1 0.45,

0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 1};

/* loop approach */

NumSamples = 2;

call randseed(54321);

do i = 1 to NumSamples;

X = RandMVOrdinal(500, P, Delta);

/* do something with each sample */

end;

/* print results */

c=varNames;

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

quit;

many thanks

Re: simulation multivariate ordinal data with 10 variables

thanoon — Sat, 22 Feb 2014 15:52:55 GMT

dear dr.

i still have some errors after putting the previous code can you correct it to me please

proc iml;

load module=_all_; /* load the modules */

/* P1 P2 P3 p4 p5 p6 p7 p8 p9 p10 */

P = {0.35 0.50 0.20 0.10 0.10 0.30 0.20 0.25 0.15 0.20,

0.30 0.10 0.20 0.30 0.20 0.20 0.40 0.05 0.45 0.10,

0.15 0.20 0.35 0.25 0.50 0.20 0.25 0.55 0.10 0.10,

0.20 0.20 0.25 0.35 0.20 0.30 0.15 0.15 0.30 0.60};

/* expected values and variance for each ordinal variable */

Expected = Mean(P) // Var(P);

varNames = "X1":"X10";

print Expected[r={"Mean" "Var"} c=varNames];

/* test the RandMVOrd function */

Delta = {1 0.45 0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05,

0.45 1 0.45 0.4 0.35 0.3 0.25 0.2 0.15 0.1,

0.4 0.45 1 0.45 0.4 0.35 0.3 0.25 0.2 0.15,

0.35 0.4 0.45 1 0.45 0.4 0.35 0.3 0.25 0.2,

0.3 0.35 0.4 0.45 1 0.45 0.4 0.35 0.3 0.25,

0.25 0.3 0.35 0.4 0.45 1 0.45 0.4 0.35 0.3,

0.2 0.25 0.3 0.35 0.4 0.45 1 0.45 0.4 0.35,

0.15 0.2 0.25 0.3 0.35 0.4 0.45 1 0.45 0.4,

0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 1 0.45,

0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 1};

/* loop approach */

NumSamples = 2;

call randseed(54321);

do i = 1 to NumSamples;

X = RandMVOrdinal(500, P, Delta);

/* do something with each sample */

end;

/* print results */

c=varNames;

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

quit;

many thanks

Re: simulation multivariate ordinal data with 10 variables

SteveDenham — Mon, 24 Feb 2014 14:03:02 GMT

Without the log, it is impossible to diagnose errors. With the log, you should be able to identify critical points, and suggest yourself what might be done. That would be much more likely to draw helpful responses than just firing code at the forum, and saying "I have errors."

Steve Denham

Re: simulation multivariate ordinal data with 10 variables

thanoon — Mon, 24 Feb 2014 15:01:34 GMT

thanks alot Mr. Steve

this is the log

1 The SAS System 17:52 Monday, February 24, 2014

1 ;*';*";*/;quit;run;

2 OPTIONS PAGENO=MIN;

3 %LET _CLIENTTASKLABEL='222222222 after intiqam multi samples';

4 %LET _CLIENTPROJECTPATH='';

5 %LET _CLIENTPROJECTNAME='';

6 %LET _SASPROGRAMFILE='F:\sas simulation final\sas cods program\222222222 after intiqam multi samples.sas';

8 ODS _ALL_ CLOSE;

9 OPTIONS DEV=ACTIVEX;

10 GOPTIONS XPIXELS=0 YPIXELS=0;

11 FILENAME EGSR TEMP;

12 ODS tagsets.sasreport13(ID=EGSR) FILE=EGSR STYLE=HtmlBlue

12 ! STYLESHEET=(URL="file:///C:/Program%20Files/SASHome/SASEnterpriseGuide/5.1/Styles/HtmlBlue.css") NOGTITLE NOGFOOTNOTE

12 ! GPATH=&sasworklocation ENCODING=UTF8 options(rolap="on");

NOTE: Writing TAGSETS.SASREPORT13(EGSR) Body file: EGSR

14 GOPTIONS ACCESSIBLE;

15 proc iml;

WARNING: The SAS/IML product with which IML (2) is associated will be expiring soon, and is currently in warning mode to indicate

this upcoming expiration. Please run PROC SETINIT to obtain more information on your warning period.

NOTE: IML Ready

16 load module=_all_;

NOTE: Opening storage library WORK.IMLSTOR

16 ! /* load the modules */

17 /* P1 P2 P3 p4 p5 p6 p7 p8 p9 p10 */

18 P = {0.35 0.50 0.20 0.10 0.10 0.30 0.20 0.25 0.15 0.20,

19 0.30 0.10 0.20 0.30 0.20 0.20 0.40 0.05 0.45 0.10,

20 0.15 0.20 0.35 0.25 0.50 0.20 0.25 0.55 0.10 0.10,

21 0.20 0.20 0.25 0.35 0.20 0.30 0.15 0.15 0.30 0.60};

24 /* expected values and variance for each ordinal variable */

25 Expected = Mean(P) // Var(P);

26 varNames = "X1":"X10";

27 print Expected[r={"Mean" "Var"} c=varNames];

28 /* test the RandMVOrd function */

29 Delta = {1 0.45 0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05,

30 0.45 1 0.45 0.4 0.35 0.3 0.25 0.2 0.15 0.1,

31 0.4 0.45 1 0.45 0.4 0.35 0.3 0.25 0.2 0.15,

32 0.35 0.4 0.45 1 0.45 0.4 0.35 0.3 0.25 0.2,

33 0.3 0.35 0.4 0.45 1 0.45 0.4 0.35 0.3 0.25,

34 0.25 0.3 0.35 0.4 0.45 1 0.45 0.4 0.35 0.3,

35 0.2 0.25 0.3 0.35 0.4 0.45 1 0.45 0.4 0.35,

36 0.15 0.2 0.25 0.3 0.35 0.4 0.45 1 0.45 0.4,

37 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 1 0.45,

38 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 1};

39 /* loop approach */

40 NumSamples = 10;

41 call randseed(54321);

42 do i = 1 to NumSamples;

43 X = RandMVOrdinal(1000, P, Delta);

44 /* do something with each sample */

45 end;

ERROR: Invocation of unresolved module RANDMVORDINAL.

statement : ASSIGN at line 43 column 4

46 /* print results */

47 c=varNames;

2 The SAS System 17:52 Monday, February 24, 2014

48 create MVO from X[colname=c];

ERROR: Matrix X has not been set to a value.

statement : CREATE at line 48 column 1

48 ! append from X;

ERROR: No data set is currently open for output.

statement : APPEND at line 48 column 32

48 ! close MVO;

NOTE: Cannot close WORK.MVO; it is not open.

49 quit;

NOTE: Exiting IML.

NOTE: Storage library WORK.IMLSTOR closed.

NOTE: The SAS System stopped processing this step because of errors.

NOTE: PROCEDURE IML used (Total process time):

real time 0.90 seconds

cpu time 0.04 seconds

51 GOPTIONS NOACCESSIBLE;

52 %LET _CLIENTTASKLABEL=;

53 %LET _CLIENTPROJECTPATH=;

54 %LET _CLIENTPROJECTNAME=;

55 %LET _SASPROGRAMFILE=;

57 ;*';*";*/;quit;run;

58 ODS _ALL_ CLOSE;

61 QUIT; RUN;

Re: simulation multivariate ordinal data with 10 variables

SteveDenham — Mon, 24 Feb 2014 17:43:05 GMT

The first thing I would check is whether or not the module RANDMVORDINAL is correctly saved in IMLSTOR. The error statement implies that it is not present at execution, which in turn implies that it is not in the store. Go back to where you created the module and make sure that there are no errors associated with it, AND that it has been stored correctly.

Steve Denham

Message was edited by: Steve Denham

Re: simulation multivariate ordinal data with 10 variables

Rick_SAS — Mon, 24 Feb 2014 18:54:45 GMT

You can use

SHOW MODULES;

to see what modules are loaded.

Re: simulation multivariate ordinal data with 10 variables

thanoon — Wed, 26 Feb 2014 14:13:12 GMT

thanks alot doctor rick

i wrote this command SHOW MODULES in sas program and got on same results but i think the problem in loop command.

1 The SAS System 16:57 Wednesday, February 26, 2014

1 ;*';*";*/;quit;run;

2 OPTIONS PAGENO=MIN;

3 %LET _CLIENTTASKLABEL='222222222 after intiqam multi samples';

4 %LET _CLIENTPROJECTPATH='';

5 %LET _CLIENTPROJECTNAME='';

6 %LET _SASPROGRAMFILE='F:\sas simulation final\sas cods program\222222222 after intiqam multi samples.sas';

8 ODS _ALL_ CLOSE;

9 OPTIONS DEV=ACTIVEX;

10 GOPTIONS XPIXELS=0 YPIXELS=0;

11 FILENAME EGSR TEMP;

12 ODS tagsets.sasreport13(ID=EGSR) FILE=EGSR STYLE=HtmlBlue

12 ! STYLESHEET=(URL="file:///C:/Program%20Files/SASHome/SASEnterpriseGuide/5.1/Styles/HtmlBlue.css") NOGTITLE NOGFOOTNOTE

12 ! GPATH=&sasworklocation ENCODING=UTF8 options(rolap="on");

NOTE: Writing TAGSETS.SASREPORT13(EGSR) Body file: EGSR

14 GOPTIONS ACCESSIBLE;

15 proc iml;

NOTE: IML Ready

16 SHOW MODULES;

NOTE: No modules are currently defined.

18 /* P1 P2 P3 p4 p5 p6 p7 p8 p9 p10 */

19 P = {0.35 0.50 0.20 0.10 0.10 0.30 0.20 0.25 0.15 0.20,

20 0.30 0.10 0.20 0.30 0.20 0.20 0.40 0.05 0.45 0.10,

21 0.15 0.20 0.35 0.25 0.50 0.20 0.25 0.55 0.10 0.10,

22 0.20 0.20 0.25 0.35 0.20 0.30 0.15 0.15 0.30 0.60};

25 /* expected values and variance for each ordinal variable */

26 Expected = Mean(P) // Var(P);

27 varNames = "X1":"X10";

28 print Expected[r={"Mean" "Var"} c=varNames];

29 /* test the RandMVOrd function */

30 Delta = {1 0.45 0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05,

31 0.45 1 0.45 0.4 0.35 0.3 0.25 0.2 0.15 0.1,

32 0.4 0.45 1 0.45 0.4 0.35 0.3 0.25 0.2 0.15,

33 0.35 0.4 0.45 1 0.45 0.4 0.35 0.3 0.25 0.2,

34 0.3 0.35 0.4 0.45 1 0.45 0.4 0.35 0.3 0.25,

35 0.25 0.3 0.35 0.4 0.45 1 0.45 0.4 0.35 0.3,

36 0.2 0.25 0.3 0.35 0.4 0.45 1 0.45 0.4 0.35,

37 0.15 0.2 0.25 0.3 0.35 0.4 0.45 1 0.45 0.4,

38 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 1 0.45,

39 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 1};

40 /* loop approach */

41 NumSamples = 10;

42 call randseed(54321);

43 do i = 1 to NumSamples;

44 X = RandMVOrdinal(1000, P, Delta);

45 /* do something with each sample */

46 end;

ERROR: Invocation of unresolved module RANDMVORDINAL.

statement : ASSIGN at line 44 column 4

47 /* print results */

48 c=varNames;

49 create MVO from X[colname=c];

ERROR: Matrix X has not been set to a value.

2 The SAS System 16:57 Wednesday, February 26, 2014

statement : CREATE at line 49 column 1

49 ! append from X;

ERROR: No data set is currently open for output.

statement : APPEND at line 49 column 32

49 ! close MVO;

NOTE: Cannot close WORK.MVO; it is not open.

50 quit;

NOTE: Exiting IML.

NOTE: The SAS System stopped processing this step because of errors.

NOTE: PROCEDURE IML used (Total process time):

real time 0.27 seconds

cpu time 0.03 seconds

52 GOPTIONS NOACCESSIBLE;

53 %LET _CLIENTTASKLABEL=;

54 %LET _CLIENTPROJECTPATH=;

55 %LET _CLIENTPROJECTNAME=;

56 %LET _SASPROGRAMFILE=;

58 ;*';*";*/;quit;run;

59 ODS _ALL_ CLOSE;

62 QUIT; RUN;

Re: simulation multivariate ordinal data with 10 variables

SteveDenham — Wed, 26 Feb 2014 19:58:36 GMT

That indicates that it is not in IMLSTOR. Go back to where you created the module RANDMVORDINAL and make sure that there are no errors associated with it, AND that it has been stored correctly.

Steve Denham

Re: simulation multivariate ordinal data with 10 variables

thanoon — Fri, 28 Feb 2014 01:13:55 GMT

dear mr. denham

i dont find where is the error in sas program.