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Deep tobit model: an integrated framework for high-dimensional censored regression with variable selection

Tong Wu et al.

Lifetime Data Analysis: an international journal devoted to the methods and applications of reliability and survival analysis2026https://doi.org/10.1007/s10985-026-09690-5article
ABDC B
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0.50

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https://doi.org/https://doi.org/10.1007/s10985-026-09690-5

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@article{tong2026,
  title        = {{Deep tobit model: an integrated framework for high-dimensional censored regression with variable selection}},
  author       = {Tong Wu et al.},
  journal      = {Lifetime Data Analysis: an international journal devoted to the methods and applications of reliability and survival analysis},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1007/s10985-026-09690-5},
}

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Deep tobit model: an integrated framework for high-dimensional censored regression with variable selection

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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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