Exact tests for the means of Gaussian stochastic processes

Andrea Ghiglietti; Anna Maria Paganoni

doi:10.1016/j.spl.2017.08.001

Exact tests for the means of Gaussian stochastic processes

Andrea Ghiglietti^*, Anna Maria Paganoni

^*Autore corrispondente per questo lavoro

Polytechnic University of Milan

Risultato della ricerca: Contributo in rivista › Articolo in rivista › peer review

3 Citazioni (Scopus)

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.

Lingua originale	English
pagine (da-a)	102-107
Numero di pagine	6
Rivista	STATISTICS & PROBABILITY LETTERS
Volume	131
DOI	https://doi.org/10.1016/j.spl.2017.08.001
Stato di pubblicazione	Pubblicato - 2017
Pubblicato esternamente	Sì

Keywords

Distances in L2
Functional data
Gaussian processes
Inference on the mean
Power of exact tests

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10.1016/j.spl.2017.08.001

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title = "Exact tests for the means of Gaussian stochastic processes",

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 = "Distances in L2, Functional data, Gaussian processes, Inference on the mean, Power of exact tests, Distances in L2, Functional data, Gaussian processes, Inference on the mean, Power of exact tests",

author = "Andrea Ghiglietti and Paganoni, {Anna Maria}",

year = "2017",

doi = "10.1016/j.spl.2017.08.001",

language = "English",

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AU - Ghiglietti, Andrea

AU - Paganoni, Anna Maria

PY - 2017

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N2 - 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.

AB - 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.

KW - Distances in L2

KW - Functional data

KW - Gaussian processes

KW - Inference on the mean

KW - Power of exact tests

KW - Distances in L2

KW - Functional data

KW - Gaussian processes

KW - Inference on the mean

KW - Power of exact tests

UR - http://hdl.handle.net/10807/109393

UR - http://www.sciencedirect.com/science/article/pii/s0167715217302614

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DO - 10.1016/j.spl.2017.08.001

M3 - Article

SN - 0167-7152

VL - 131

SP - 102

EP - 107

JO - STATISTICS & PROBABILITY LETTERS

JF - STATISTICS & PROBABILITY LETTERS

ER -

Exact tests for the means of Gaussian stochastic processes

Abstract

Keywords

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