Goodness-of-fit testing for the error distribution in functional linear models
By: Natalie Neumeyer, Leonie Selk
Potential Business Impact:
Finds if math models fit real data.
We consider the error distribution in functional linear models with scalar response and functional covariate. Different asymptotic expansions of the empirical distribution function and the empirical characteristic function based on estimated residuals under different model assumptions are discussed. The results are applied for simple and composite goodness-of-fit testing for the error distribution, in particular testing for normal distribution.
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