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Creators/Authors contains: "Horváth, Lajos"

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  1. ; ; (, Journal of Econometrics)
    Free, publicly-accessible full text available July 1, 2026
  2. ; ; (, Journal of Business & Economic Statistics)
    Full Text Available 
  3. ; ; (, TEST)
    Full Text Available 
  4. ; ; ; (, Journal of Time Series Analysis)
    Full Text Available 
  5. ; ; (, The Annals of Statistics)
    Full Text Available 
  6. ; ; (, Journal of Multivariate Analysis)
    Full Text Available 
  7. ; ; (, International Statistical Review)
    Summary The paper is concerned with testing normality in samples of curves and error curves estimated from functional regression models. We propose a general paradigm based on the application of multivariate normality tests to vectors of functional principal components scores. We examine finite sample performance of a number of such tests and select the best performing tests. We apply them to several extensively used functional data sets and determine which can be treated as normal, possibly after a suitable transformation. We also offer practical guidance on software implementations of all tests we study and develop large sample justification for tests based on sample skewness and kurtosis of functional principal component scores. 
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