Monte Carlo Techniques in Studying Robust Estimators

David C. Hoaglin

No 16, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: Recent work on robust estimation has led to many procedures, which are easy to formulate and straightforward to program but difficult to study analytically. In such circumstances experimental sampling is quite attractive, but the variety and complexity of both estimators and sampling situations make effective Monte Carlo techniques essential. This discussion examines problems, techniques, and results and draws on examples in studies of robust location and robust regression.

Date: 1973-11
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