Gillard, Jonathan ![]() ![]() ![]() |
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Official URL: http://dx.doi.org/10.1016/j.amc.2017.05.050
Abstract
We consider the problem of estimating the optimal direction in regression by maximizing the probability that the scalar product between the vector of unknown parameters and the chosen direction is positive. The estimator maximizing this probability is simple in form, and is especially useful for situations where the number of parameters is much larger than the number of observations. We provide examples which show that this estimator is superior to state-of-the-art methods such as the LASSO for estimating the optimal direction.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Mathematics |
Subjects: | Q Science > QA Mathematics |
Uncontrolled Keywords: | Random balance; Screening experiments; Box–Wilson methodology; LASSO; Ridge regression |
Publisher: | Elsevier |
ISSN: | 0096-3003 |
Date of First Compliant Deposit: | 1 June 2017 |
Date of Acceptance: | 14 May 2017 |
Last Modified: | 09 Nov 2023 18:05 |
URI: | https://orca.cardiff.ac.uk/id/eprint/101058 |
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