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Everything about Robust regression

Specialized form of regression analysis, in statistics

In robust statistics, robust regression seeks to overcome some limitations of traditional regression analysis. A regression analysis models the relationship between one or more independent variables and a dependent variable. Standard types of regression, such as ordinary least squares, have favourable properties if their underlying assumptions are true, but can give misleading results otherwise. Robust regression methods are designed to limit the effect that violations of assumptions by the underlying data-generating process have on regression estimates. Wikipedia →

🧭 Start here: a 6-step reading path

  1. Read the overview: Robust regressionA 5-minute orientation
  2. Skim a recent paper: Robust multi-view learning via adaptive regressionInfluential work since 2022
  3. Pick up a classic book: Robust diagnostic regression analysisThe most-reprinted book on the subject
  4. Read the landmark paper: Robust Locally Weighted Regression and Smoothing ScatterplotsCited 14,994 times
  5. Go sideways: Heteroskedasticity-consistent standard errorsA closely related topic
  6. Go sideways: Studentized residualA closely related topic

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🏆 Landmark papers (most cited)

🆕 Influential since 2022

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