3 papers
stat.AP2025
A Practical Introduction to Regression-based Causal Inference in Meteorology (I): All confounders measured
Caren Marzban, Yikun Zhang, Nicholas Bond +1
Whether a variable is the cause of another, or simply associated with it, is often an important scientific question. Causal Inference is the name associated with the body of techni…
stat.AP2025
A Practical Introduction to Regression-based Causal Inference in Meteorology (II): Unmeasured confounders
Caren Marzban, Yikun Zhang, Nicholas Bond +1
One obstacle to ``elevating'' correlation to causation is the phenomenon of confounding, i.e., when a correlation between two variables exists because both variables are in fact ca…
stat.ME2024
Principal Component Analysis for Equation Discovery
Caren Marzban, Ulvi Yurtsever, Michael Richman
Principal Component Analysis (PCA) is one of the most commonly used statistical methods for data exploration, and for dimensionality reduction wherein the first few principal compo…