IMPROVED BOUNDS FOR SMALL-SAMPLE ESTIMATION

被引：14

作者：

Gratton, Serge ^{[1
]}

Titley-Peloquin, David ^{[2
]}

机构：

[1] Univ Toulouse, INPT IRIT ENSEEIHT, F-31071 Toulouse, France

[2] McGill Univ, Dept Bioresource Engn, Montreal, PQ H3A O39, Canada

来源：

SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS | 2018年 / 39卷 / 02期

关键词：

statistical estimation; small-sample estimation; norm estimation; condition number estimation; STATISTICAL CONDITION ESTIMATION; GAUSSIAN-PROCESSES; CONDITION NUMBERS;

D O I：

10.1137/17M1137541

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

We derive improved error bounds for small-sample statistical estimation of the matrix Frobenius norm. The bounds rigorously establish that small-sample estimators provide reliable order-of-magnitude estimates of norms and condition numbers, for matrices of arbitrary rank, even when very few random samples are used.

引用

页码：922 / 931

页数：10

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