Exact tests for the means of Gaussian stochastic processes

Andrea Ghiglietti and Anna Maria Paganoni

Statistics & Probability Letters, 2017, vol. 131, issue C, 102-107

Abstract: This paper investigates the inferential properties of testing the means of Gaussian functional data, using a Mahalanobis type distance for Hilbert spaces. We establish the analytic power of exact and asymptotic tests, for the known and unknown covariance case, respectively.

Keywords: Functional data; Inference on the mean; Power of exact tests; Gaussian processes; Distances in L2 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.spl.2017.08.001

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