On estimating the mean function of a Gaussian process

DOI10.1016/0167-7152(94)90071-XzbMath0793.62022OpenAlexW2048974304MaRDI QIDQ1324593

P. Anilkumar

Publication date: 24 May 1994

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-7152(94)90071-x

zbMATH Keywords

Gaussian processreproducing kernel Hilbert spaceBayes estimatorsCramér-Rao boundestimating functionmean functionsieve estimationknown covariance function

Mathematics Subject Classification ID

Bayesian inference (62F15) Nonparametric statistical resampling methods (62G09) Applications of functional analysis in probability theory and statistics (46N30)

Related Items (2)

Asymptotics for the nonparametric estimation of the mean function of a random process ⋮ RELIABILITY CENTERED MULTI OBJECTIVE HYBRID FLOW SHOP SCHEDULING

Cites Work

• A sieve estimator for the mean of a Gaussian process
• Optimal unbiased statistical estimating functions for Hilbert space valued parameters
• On Convergence Rates in Nonparametric Problems
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