An estimation technique which is insensitive to small departures from the idealized assumptions which have been used to optimize the algorithm. Classes of such techniques include M-estimates (which follow from maximum likelihood considerations), L-Estimates (which are linear combinations of order statistics), and R-Estimates (based on statistical rank tests).
Robust Estimation
See also
L-Estimate, M-Estimate, R-EstimateExplore with Wolfram|Alpha
References
Press, W. H.; Flannery, B. P.; Teukolsky, S. A.; and Vetterling, W. T. "Robust Estimation." §15.7 in Numerical Recipes in FORTRAN: The Art of Scientific Computing, 2nd ed. Cambridge, England: Cambridge University Press, pp. 694-700, 1992.Referenced on Wolfram|Alpha
Robust EstimationCite this as:
Weisstein, Eric W. "Robust Estimation." From MathWorld--A Wolfram Resource. https://mathworld.wolfram.com/RobustEstimation.html