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A robust weighted Liu regression framework for addressing multicollinearity and outliers

R. Muthukrishnan & Karthika Ramakrishnan

Quality & Quantity2026https://doi.org/10.1007/s11135-025-02555-3article
ABDC B
Weight
0.50

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https://doi.org/https://doi.org/10.1007/s11135-025-02555-3

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@article{r.2026,
  title        = {{A robust weighted Liu regression framework for addressing multicollinearity and outliers}},
  author       = {R. Muthukrishnan & Karthika Ramakrishnan},
  journal      = {Quality & Quantity},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1007/s11135-025-02555-3},
}

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A robust weighted Liu regression framework for addressing multicollinearity and outliers

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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