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.
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页码：77 / 84
页数：8
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