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Title: Robust regression on noisy data for fusion scaling laws

We introduce the method of geodesic least squares (GLS) regression for estimating fusion scaling laws. Based on straightforward principles, the method is easily implemented, yet it clearly outperforms established regression techniques, particularly in cases of significant uncertainty on both the response and predictor variables. We apply GLS for estimating the scaling of the L-H power threshold, resulting in estimates for ITER that are somewhat higher than predicted earlier.
Authors:
 [1] ;  [2]
  1. Department of Applied Physics, Ghent University, B-9000 Ghent (Belgium)
  2. (LPP-ERM/KMS), Ecole Royale Militaire - Koninklijke Militaire School, B-1000 Brussels (Belgium)
Publication Date:
OSTI Identifier:
22308659
Resource Type:
Journal Article
Resource Relation:
Journal Name: Review of Scientific Instruments; Journal Volume: 85; Journal Issue: 11; Other Information: (c) 2014 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES; 46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY; EVALUATION; FORECASTING; ITER TOKAMAK; LEAST SQUARE FIT; SIMULATION