Statistical inference for stochastic processes: Two-sample hypothesis tests

Andrea Ghiglietti, Francesca Ieva, Anna Maria Paganoni

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8 Citazioni (Scopus)

Abstract

In this paper, we present inferential procedures to compare the means of two samples of functional data. The proposed tests are based on a suitable generalization of Mahalanobis distance to the Hilbert space of square integrable functions defined on a compact interval. The only conditions required concern the moments and the independence of the functional data, while the distribution of the processes generating the data is not needed to be specified. Test procedures are proposed for both the cases of known and unknown variance–covariance structures, and asymptotic properties of test statistics are deeply studied. A simulation study and a real case data analysis are also presented.
Lingua originaleEnglish
pagine (da-a)49-68
Numero di pagine20
RivistaJournal of Statistical Planning and Inference
Volume180
DOI
Stato di pubblicazionePubblicato - 2017
Pubblicato esternamente

Keywords

  • Distances in L2
  • Functional data
  • Hypothesis tests
  • Two-sample problems

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