article Open Access
The robust regression estimators: Performance & evaluation
International Journal of Statistics and Applied Mathematics · 2023 · Vol. 8(6) · pp. 83–87
P Anandhi✉(Periyar University)S Mohan Prabhu(Statistical Service)
Abstract
Ordinary Least Square (OLS) estimates for a linear model are extremely sensitive to odd values in the design space or outliers among unpredicted values. Even a single value can have a significant impact on parameter estimations. This study focuses on, reviews, and describes different existing and popular robust regression approaches, as well as compares their efficiency. Recent advances in robust regression algorithms are also presented.
Advanced Statistical Methods and ModelsFault Detection and Control SystemsAdvanced Statistical Process MonitoringRobust regressionOutlierOrdinary least squaresEstimatorLinear regressionRegressionStatisticsEconometricsRegression analysisRobust statistics
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