Quadratic progamming and penalised regression

Andrew D A C Smith

Research output: Contribution to journalArticle (Academic Journal)peer-review

Abstract

Quadratic programming is a versatile tool for calculating estimates in penalized regression. It can be used to produce estimates based on L 1 roughness penalties, as in total variation denoising. In particular, it can calculate estimates when the roughness penalty is the total variation of a derivative of the estimate. Combining two roughness penalties, the total variation and total variation of the third derivative, results in an estimate with continuous second derivative but controls the number of spurious local extreme values. A multiresolution criterion may be included in a quadratic program to achieve local smoothing without having to specify smoothing parameters.
Original languageEnglish
Pages (from-to)1363-1372
Number of pages10
JournalCommunications in Statistics - Theory and Methods
Volume42
Issue number4
Early online date26 Feb 2013
DOIs
Publication statusPublished - 2013

Fingerprint

Dive into the research topics of 'Quadratic progamming and penalised regression'. Together they form a unique fingerprint.

Cite this