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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Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:131:y:2017:i:c:p:102-107
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DOI: 10.1016/j.spl.2017.08.001
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