Simultaneous Denoising and Heterogeneity Learning for Time Series Data
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DOI: 10.1007/s12561-023-09384-8
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- Weibin Mo & Zhengling Qi & Yufeng Liu, 2021. "Rejoinder: Learning Optimal Distributionally Robust Individualized Treatment Rules," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(534), pages 699-707, April.
- Robert Tibshirani & Guenther Walther & Trevor Hastie, 2001. "Estimating the number of clusters in a data set via the gap statistic," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(2), pages 411-423.
- Zhengling Qi & Dacheng Liu & Haoda Fu & Yufeng Liu, 2020. "Multi-Armed Angle-Based Direct Learning for Estimating Optimal Individualized Treatment Rules With Various Outcomes," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(530), pages 678-691, April.
- Hempstead, Katherine, 2006. "The geography of self-injury: Spatial patterns in attempted and completed suicide," Social Science & Medicine, Elsevier, vol. 62(12), pages 3186-3196, June.
- Robert Tibshirani & Michael Saunders & Saharon Rosset & Ji Zhu & Keith Knight, 2005. "Sparsity and smoothness via the fused lasso," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(1), pages 91-108, February.
- Weibin Mo & Zhengling Qi & Yufeng Liu, 2021. "Learning Optimal Distributionally Robust Individualized Treatment Rules," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(534), pages 659-674, April.
- Xu Gao & Weining Shen & Jing Ning & Ziding Feng & Jianhua Hu, 2022. "Addressing patient heterogeneity in disease predictive model development," Biometrics, The International Biometric Society, vol. 78(3), pages 1045-1055, September.
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Cancer mortality; Clustering; K-means; Sequential data; Trend filtering;All these keywords.
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