Parametric estimation for the mean of a Gaussian process by the method of sieves

DOI10.1016/0047-259X(88)90070-XzbMath0647.62084MaRDI QIDQ1104674

Anestis Antoniadis

Publication date: 1988

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

zbMATH Keywords

consistencyreproducing kernel Hilbert spaceGaussian random vectormethod of sievesreal separable Banach spacerestricted maximum likelihood estimatorsExponential rates of convergenceincreasing sequence of natural sievesinfinite dimensional mean parameter

Mathematics Subject Classification ID

Gaussian processes (60G15) Nonparametric estimation (62G05) Non-Markovian processes: estimation (62M09) Foundations and philosophical topics in statistics (62A01) Probability theory on linear topological spaces (60B11)

Related Items (4)

Functional autoregressive process with seasonality ⋮ Design-free estimation of variance matrices ⋮ Joint estimation of the mean and the covariance of a banach valued gaussian vector ⋮ Statistics of seasonality perturbed by time continuous processes with autoregressive representation

Cites Work

• A sieve estimator for the mean of a Gaussian process
• Large deviations of the sample mean in general vector spaces
• Nonparametric maximum likelihood estimation by the method of sieves
• Mesures cylindriques, espaces de Wiener et fonctions aléatoires gaussiennes
• The sizes of compact subsets of Hilbert space and continuity of Gaussian processes
• Gaussian measures on a Banach space
• Sample functions of the Gaussian process
• Analysis of variance on function spaces
• Joint estimation of the mean and the covariance of a banach valued gaussian vector
• A Note on the Absence of Tangencies in Gaussian Sample Paths
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Parametric estimation for the mean of a Gaussian process by the method of sieves