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|Language Reference under IML |
Base SAS Functions Accessible from SAS/IML
Has listing of functions that were used in data step/base language that can be used in IML. Here are some.
NOTE: In IML the use of a goto statement is limited to being used within a do loop. Often there are ways to avoid the use of the goto using do while.
Probability Functions
|CDF |computes cumulative distribution functions |
|LOGPDF |computes the logarithm of a probability function |
|LOGSDF |computes the logarithm of a survival function |
|PDF |computes probability density functions |
|POISSON |returns the probability from a Poisson distribution |
|PROBBETA |returns the probability from a beta distribution |
|PROBBNML |returns the probability from a binomial distribution |
|PROBBNRM |returns the probability from the bivariate normal distribution |
|PROBCHI |returns the probability from a chi-squared distribution |
|PROBF |returns the probability from an F distribution |
|PROBGAM |returns the probability from a gamma distribution |
|PROBHYPR |returns the probability from a hypergeometric distribution |
|PROBMC |returns a probability or a quantile from various distributions for multiple comparisons of means |
|PROBNEGB |returns the probability from a negative binomial distribution |
|PROBNORM |returns the probability from the standard normal distribution |
|PROBT |returns the probability from a t distribution |
|SDF |computes a survival function |
|[pic] |
Quantile Functions
|BETAINV |returns a quantile from the beta distribution |
|CINV |returns a quantile from the chi-squared distribution |
|FINV |returns a quantile from the F distribution |
|GAMINV |returns a quantile from the gamma distribution |
|PROBIT |returns a quantile from the standard normal distribution |
|TINV |returns a quantile from the t distribution |
|[pic] |
You can also use the quantile ( ) function as used before in the data step.
Operators
Addition Operator: +
Comparison Operators: < > = = ^=
Concatenation Operator, Horizontal: ||
Concatenation Operator, Vertical: //
Direct Product Operator: @
Division Operator: /
Element Maximum Operator:
Element Minimum Operator: ><
Index Creation Operator: :
Logical Operators: & | ^
Multiplication Operator, Elementwise: #
Multiplication Operator, Matrix: *
Power Operator, Elementwise: ##
Power Operator, Matrix: **
Sign Reverse Operator: -
Subscripts: [ ]
Subtraction Operator: -
Transpose Operator: ` (or you can use t( ) for transpose
There is some ability to call a SAS procedure from within IML but it doesn’t really offer much as we can’t use the results from the proc within IML.
Usage Note 33542: Calling a SAS procedure within PROC IML
|[pic] |[pic] |[pic] |[pic] |
You can call another procedure from within an IMLPlus program using a SUBMIT block in PROC IML beginning with SAS/IML 9.22 in SAS 9.2 TS2M3.
You can also use the SUBMIT block to call SAS procedures in SAS/IML Studio beginning with SAS 9.2. SAS/IML Studio is provided with SAS/IML and is documented in the SAS/IML Studio User's Guide and in SAS/IML Studio for SAS/STAT Users. Note that SAS/IML Studio was previously called SAS STAT Studio and is documented in the SAS Stat Studio User's Guide and in SAS Stat Studio for SAS/STAT Users. For information on downloading SAS/IML Studio, see the SAS/IML download page.
Example
In this example, the UNIVARIATE procedure is called within SAS/IML to compute a kernel density estimate for some randomly generated data.
The following statements generate data from a mixture of normal distributions and stores them in a matrix, X. Note that when run in SAS/IML Studio, the PROC IML statement below is not necessary and should be omitted.
proc iml;
call randseed(123);
y = j(400,1);
call randgen(y, 'normal');
z = j(100,1);
call randgen(z, 'normal', 3, 0.5);
x = y // z;
To use these values in PROC UNIVARIATE, write them to a SAS data set using CREATE and APPEND statements. These statements create data set A from matrix X.
create a var {"x"};
append;
close a;
Next, the UNIVARIATE procedure is called from within IML by using SUBMIT and ENDSUBMIT statements. The UNIVARIATE procedure creates an output data set (KerOut) that contains 401 observations.
submit;
proc univariate data=a;
var x;
histogram / kernel;
run;
endsubmit;
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