Temperature measurements in tokamak edge plasmas suffer frequently from outliers of unknown origin. Such outliers have an important unwanted influence on the estimation of parameters for edge temperature model functions in conventional least squares fits. Bayesian probability theory is applied to deal with such outliers and develop a robust procedure which performs highly satisfactorily.
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Dose et al. (2001) studied this question.
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