A recursive algorithm for discrete L1 linear estimation using the dual simplex method

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DOIResolve DOI: http://doi.org/10.1109/TSMC.1985.6313457
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TypeArticle
Journal titleIEEE Transactions on Systems, Man, and Cybernetics
ISSN0018-9472
Volume15
Issue6
Pages737742; # of pages: 6
AbstractOne of the practical problems in engineering and science is the estimation of parameters for a given experimental data. It is also often required to update the estimates as new points are added to or as old points are deleted from the given data set. For data containing wild points, parameter estimation using approximation in the L1 norm is usually recommended over other norms. It is shown that the updating of the the estimates is calculated with very little effort using parametric programming techniques, applied to an existing L1 approximation algorithm which itself uses a dual simplex method. Thus an online adaptation for this algorithm is highly desirable. Numerical results and comments are given.
Publication date
LanguageEnglish
AffiliationNational Research Council Canada
Peer reviewedYes
NRC number24911
NPARC number21273715
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Record identifier6dbdc8c1-48d1-479c-a28c-16ab1ba3dedf
Record created2015-01-20
Record modified2016-05-09
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