SPARSE VARYING COEFFICIENT MODELS FOR LONGITUDINAL DATA

By Hohsuk Noh, Byeong U. Park. 2010

52 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/4fc3669202d795bd6f6f7a890d5f5766acde5557

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Byeong U. Park
2. Young K. Lee
3. Enno Mammen
4. Eun Ryung Lee
5. Zhenhua Lin
6. Jiguo Cao
7. Liangliang Wang
8. Haonan Wang

Citations in the corpus

• Locally Sparse Estimator for Functional Linear Regression Models (2017, methodology): “The SCAD penalty function pλ(·) might be approximated by the local quadratic approximation (LQA; Fan and Li 2001) or the one-step local linear approximation (LLA; Zou and Li 2008;Noh and Park 2010).”
• Flexible generalized varying coefficient regression models (2012, methodology): “The case where fj are timevarying was treated by Hoover et al. (1998), Huang, Wu and Zhou (2002, 2004), Wang, Li and Huang (2008), and Noh and Park (2010).”
• Varying Coefficient Regression Models: A Review and New Developments (2015, methodology): “Inspired by Zou & Li (2008) and Noh & Park (2010), one may replace p .kˇj k/ in (2.6) by its onestep approximation p0 .k Ǒ .0/j k/kˇj k, where Ǒ .0/ j are suitable initial estimators of ˇj .”