According to this article on the Lund-Prescott test, the test requires computing the critical value of an F distribution and them flagging standardized residuals whose lengths that exceed that value. You could certainly implement that in SAS by using the OUTPUT statement in a regression procedure to generate the standardized residuals and then writing a DATA step to flag the Std Resid that exceed the critical value.
However, I suggest you look at the ROBUSTREG procedure, which can automatically flag outliers and high-leverage points based on robust linear models. See the Getting Started example in the ROBUSTREG documentation, which shows example data, syntax, and interpretation of the results.
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