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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

We propose a $prenet$ ($pr$oduct $e$lastic $net$), which is a newpenalization method for factor analysis models. The penalty is based on theproduct of a pair of elements in each row of the loading matrix. The prenet notonly shrinks some of the factor loadings toward exactly zero, but also enhancesthe simplicity of the loading matrix, which plays an important role in theinterpretation of the common factors. In particular, with a large amount ofprenet penalization, the estimated loading matrix possesses a perfect simplestructure, which is known as a desirable structure in terms of the simplicityof the loading matrix. Furthermore, the perfect simple structure estimation viathe prenet turns out to be a generalization of the $k$-means clustering ofvariables. On the other hand, a mild amount of the penalization approximates aloading matrix estimated by the quartimin rotation, one of the most commonlyused oblique rotation techniques. Thus, the proposed penalty bridges a gapbetween the perfect simple structure and the quartimin rotation. Monte Carlosimulation is conducted to investigate the performance of the proposedprocedure. Three real data analyses are given to illustrate the usefulness ofour penalty.

Simple structure estimation via prenet penalization