This article discusses SAS as a language and environment for statistical computing. The SAS System has developed over the past 20 years from being primarily a statistical package into providing a diversified system for managing and analyzing data. The part of SAS most appropriate for statistical computing is the interactive matrix language, SAS/IML. IML is used to illustrate tasks such as M-estimation, bootstrapping, and kernel density estimation. An extensive collection of preprogrammed statistical procedures is available in SAS to carry out more standard statistical analyses such as generalized linear models or categorical modeling.
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References
1.
Belsley, D.
, E. Kuh, and R. Welsch. 1980. Regression Diagnostics: Identifying Influential Data and Sources of Collinearity. New York: Wiley.
2.
Fox, J.
1991. Regression Diagnostics. Newbury Park, CA: Sage.
3.
Friendly, M.
1991. SAS System for Statistical Graphics. Cary, NC: SAS Institute.
4.
Hallahan, C.
1992. Proceedings of the Seventeenth Annual SAS Users Group International Conference. Cary, NC: SAS Institute.
5.
Härdle, W.
1991. Smoothing Techniques With Implementation in S. New York: Springer-Verlag.
6.
Thisted, R.
1988. Elements of Statistical Computing. New York: Chapman & Hall.
