ON ESTIMATING THE MEAN FUNCTION OF A GAUSSIAN PROCESS

被引：2

作者：

ANILKUMAR, P ^{[1
]}

机构：

[1] UNIV POONA,DEPT STAT,POONA 411007,MAHARASHTRA,INDIA

来源：

STATISTICS & PROBABILITY LETTERS | 1994年 / 19卷 / 01期

关键词：

GAUSSIAN PROCESS; REPRODUCING KERNEL HILBERT SPACE; SIEVE ESTIMATION; CRAMER-RAO BOUND; ESTIMATING FUNCTION; BAYES ESTIMATORS;

D O I：

10.1016/0167-7152(94)90071-X

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

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.

引用

页码：77 / 84

页数：8

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