Improved Bounds for Small-Sample Estimation | Zendy

Serge Gratton | Zendy; David Titley-Péloquin | Zendy

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Improved Bounds for Small-Sample Estimation

Author(s) -

Serge Gratton,

David Titley-Péloquin

Publication year - 2018

Publication title -

siam journal on matrix analysis and applications

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.268

H-Index - 101

eISSN - 1095-7162

pISSN - 0895-4798

DOI - 10.1137/17m1137541

Subject(s) - mathematics , estimator , matrix norm , rank (graph theory) , sample size determination , matrix (chemical analysis) , sample (material) , statistics , random matrix , combinatorics , eigenvalues and eigenvectors , physics , materials science , chemistry , chromatography , quantum mechanics , composite material

We derive improved error bounds for small-sample statistical estimation of the matrixFrobenius 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 whenvery few random samples are used.

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