Advance your understanding of tokamak data with practical statistical tools for energy confinement studies.
This book-length exploration focuses on how linear regression and generalized least squares are used to analyze confinement data from multiple tokamaks. It explains why simple models can fail when data are nearly colinear and shows proven techniques to improve reliability, including principal components and ridge regression. The material also introduces how to account for both discharge-to-discharge and device-to-device variation in a unified framework.
- Learn how to fit scaling laws for energy confinement and assess the impact of data structure on predictions
- See how colinearity affects estimates and how to stabilize calculations with robust methods
- Explore extensions like random coefficient models to handle inter-tokamak differences
- Understand practical guidance on designing experiments and selecting variables for reliable transport studies
Ideal for researchers and students working with fusion data, statistical modeling in physics, or any field where complex, multi-source data require careful regression analysis.-
Ideal for readers of scientific statistics applied to energy confinement and fusion research.