Posts tagged robust
Heteroscedastic Bayesian Robust Regression
- 30 April 2026
The PyMC gallery has two robust regression notebooks: one with a Student-t likelihood (pymc-examples:GLM-robust) and one with the Hogg (2010) signal-vs-noise mixture (pymc-examples:GLM-robust-with-outlier-detection). Both protect against vertical outliers (points with unusual response values), but neither defends against leverage points: observations far from the bulk of the predictor space, which can drag the regression line even under a heavy-tailed likelihood.
GLM: Robust Linear Regression
- 10 January 2023
Duplicate implicit target name: “glm: robust linear regression”.
GLM: Robust Regression using Custom Likelihood for Outlier Classification
- 17 November 2021
Using PyMC for Robust Regression with Outlier Detection using the Hogg 2010 Signal vs Noise method.