One can do Kolmogorov–Smirnov test, Cramer–von Mises test, and Anderson–Darling test in UNIVARIATE to do a distributional hypothesis test. For example, the following generates normal observations with μ=σ=10. data _;
call streaminit(1);
do i=1 to 5000;
x=rand("normal",10,10);
output;
end;
run; For these observations, one can use UNIVARIATE to check whether the observations are normal with the parameters. proc univariate;
var x;
histogram/normal(mu=10,sigma=10);
run; SAS provides some other distributions such as the beta distribution, the exponential distribution, the gamma distribution as well (http://support.sas.com/documentation/cdl/en/procstat/66703/HTML/default/procstat_univariate_syntax09.htm), but is there another way to do this for the other distributions? For example, one cannot use UNIVARIATE if the hypothetical distribution is the F distribution with d1=d2=10 as follows. data _;
call streaminit(1);
do i=1 to 5000;
x=rand("f",10,10);
output;
end;
run; I also found PROC NPAR1WAY EDF, but it provides a two-way test that compares two different samples, while I need to do the usual distribution test. Thanks in advance.
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