Testing normality of spatially indexed functional data

Siegfried Hörmann, Piotr Kokoszka*, Thomas Kuenzer

*Corresponding author for this work

Research output: Contribution to journalArticle

Abstract

We develop a test of normality for spatially indexed functions. The assumption of normality is common in spatial statistics, yet no significance tests, or other means of assessment, have been available for functional data. This article aims at filling this gap in the case of functional observations on a spatial grid. Our test compares the moments of the spatial (frequency domain) principal component scores to those of a suitable Gaussian distribution. Critical values can be readily obtained from a chi-squared distribution. We provide rigorous theoretical justification for a broad class of weakly stationary functional random fields. We perform simulation studies to assess the power of the test against various alternatives. An application to surface incoming shortwave radiation illustrates the practical value of this procedure.

Original languageEnglish
JournalThe Canadian Journal of Statistics
DOIs
Publication statusAccepted/In press - 7 Oct 2021

Keywords

  • Functional data
  • normality test
  • principal components
  • spatial statistics

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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