English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This article is concerned with the Bridge Regression, which is a specialfamily in penalized regression with penalty function$\sum_{j=1}^{p}|\beta_j|^q$ with $q>0$, in a linear model with linearrestrictions. The proposed restricted bridge (RBRIDGE) estimator simultaneouslyestimates parameters and selects important variables when a prior informationabout parameters are available in either low dimensional or high dimensionalcase. Using local quadratic approximation, the penalty term can be approximatedaround a local initial values vector and the RBRIDGE estimator enjoys aclosed-form expression which can be solved when $q>0$. Special cases of ourproposal are the restricted LASSO ($q=1$), restricted RIDGE ($q=2$), andrestricted Elastic Net ($1< q < 2$) estimators. We provide some theoreticalproperties of the RBRIDGE estimator under for the low dimensional case, whereasthe computational aspects are given for both low and high dimensional cases. Anextensive Monte Carlo simulation study is conducted based on different priorpieces of information and the performance of the RBRIDGE estiamtor is comparedwith some competitive penalty estimators as well as the ORACLE. We alsoconsider four real data examples analysis for comparison sake. The numericalresults show that the suggested RBRIDGE estimator outperforms outstandinglywhen the prior is true or near exact

Penalized regression via the restricted bridge estimator