Performance of LAD-LASSO and WLAD-LASSO on High Dimensional Regression in Handling Data Containing Outliers

Performance of LAD-LASSO and WLAD-LASSO on High Dimensional Regression in Handling Data Containing Outliers

In several research areas, it is common to have a dataset with more explanatory variables than the number of observations, called high-dimensional data. This condition can lead to multicollinearity problem. The least absolute shrinkage and selection operator (LASSO) solves the problem by shrinking t...

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Bibliographic Details
Main Authors: Septa Dwi Cahya, Bagus Sartono, Indahwati Indahwati, Evita Purnaningrum
Format: Article
Language:English
Published: Universitas Muhammadiyah Mataram 2022-10-01
Series:JTAM (Jurnal Teori dan Aplikasi Matematika)
Subjects:
high dimensional data
lad-lasso
multicollinearity
outliers
wlad-lasso.
Online Access:http://journal.ummat.ac.id/index.php/jtam/article/view/8968

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