On estimating the mean function of a Gaussian process

P. Anilkumar

Statistics & Probability Letters, 1994, vol. 19, issue 1, 77-84

Abstract: A new estimator is proposed for the mean function of a Gaussian process with known covariance function. The estimator m(t) is interpreted from a Bayesian point of view. It is shown that the estimator is minimax within a certain subset of the parameter space.

Keywords: Gaussian; process; reproducing; kernel; Hilbert; space; sieve; estimation; Cramer--Rao; bound; estimating; function; Bayes; estimators (search for similar items in EconPapers)
Date: 1994
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