How to Make Linear Regression Survive Outliers
Data ScienceHow to Make Linear Regression Survive OutliersRobust Estimation Series: comparing classical and modern robust estimators through theory, code, and experimentsAamir Hussain Chughtai, PhDSeptember 16, 202627 min readA few outliers can pull a regression line off course. Yet linear models remain valuable when coefficients need a physical interpretation, predictions must run on a resource-constrained device, computational latency matters, or a simple benchmark is needed before introducing a higher-capacity model. A faulty sensor, communication error, calibration problem, or biased measurement can produce observations far from the relationship we actually want to estimate.
- ▪Data ScienceHow to Make Linear Regression Survive OutliersRobust Estimation Series: comparing classical and modern robust estimators through theory, code, and experimentsAamir Hussain Chughtai, PhDSeptember 16, 202627 min readA few outliers
- ▪Yet linear models remain valuable when coefficients need a physical interpretation, predictions must run on a resource-constrained device, computational latency matters, or a simple benchmark is needed before introducing a higher-capacity m
- ▪A faulty sensor, communication error, calibration problem, or biased measurement can produce observations far from the relationship we actually want to estimate.
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| Publication time | Wed, 16 Sep 2026 15:30:01 GMT |
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Data ScienceHow to Make Linear Regression Survive OutliersRobust Estimation Series: comparing classical and modern robust estimators through theory, code, and experimentsAamir Hussain Chughtai, PhDSeptember 16, 202627 min readA few outliers can pull a regression line off course. Robust estimation helps keep the underlying trend in focus.How to Make Linear Regression Survive Outliers; Comparing Classical and Modern Robust Estimators Through Theory, Code, and ExperimentsA simple model with a serious weaknessA straight line can look surprisingly convincing—until a few bad measurements pull it somewhere it should never have gone.Linear regression is often one of the first predictive models practitioners learn—and one of the first they set aside when more sophisticated machine-learning methods…
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