Title
Total Least Squares And Chebyshev Norm
Abstract
We investigate the total least square problem (TLS) with Chebyshev norm instead of the traditionally used Frobenius norm. The use of Chebyshev norm is motivated by the need for robust solutions. In order to solve the problem, we introduce interval computation and use many of the results obtained there. We show that the problem we are tackling is NP-hard in general, but it becomes polynomial in the case of a fixed number of regressors. This is the most important practical result since usually we work with regression models with a low number of regression parameters (compared to the number of observations). We present not only a precise algorithm for the problem, but also a computationally efficient heuristic. We illustrate the behavior of our method in a particular probabilistic setup by a simulation study.
Year
DOI
Venue
2015
10.1016/j.procs.2015.05.393
INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE, ICCS 2015 COMPUTATIONAL SCIENCE AT THE GATES OF NATURE
Keywords
Field
DocType
Total least squares, Chebyshev norm, interval computation, computational complexity
Least squares,Chebyshev nodes,Mathematical optimization,Computer science,Matrix norm,Chebyshev filter,Interval arithmetic,Total least squares,Computational complexity theory,Chebyshev iteration
Conference
Volume
ISSN
Citations 
51
1877-0509
0
PageRank 
References 
Authors
0.34
8
2
Name
Order
Citations
PageRank
Milan Hladík126836.33
Michal Černý2205.12