Nonparametric regression methods for longitudinal data analysis
By Hulin Wu, Jin-Ting Zhang. 2006
202 citations recorded by the source corpus.
Subfields: Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/0c3837d9e2f3c6e5e336c129baad1875809bbbb9
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In Statistics and Probability
- Jianhua Z. Huang
- Hua Liang
- Ganggang Xu
- Tao Lu
- Hongqi Xue
- J. Schwarze
- Andrea Wiencierz
- Christoph Wunder
Citations in the corpus
- Asymptotic optimality and efficient computation of the leave-subject-out cross-validation (2012, background): “, Zeger and Diggle (1994), Zhang et al. (1998), Lin and Ying (2001), Wang, Carroll and Lin (2005)] and nonparametric [e.”
- Well-Being over the Life Span: Semiparametric Evidence from British and German Longitudinal Data (2009, methodology): “equally spaced sample quantiles method (for details, cf. Wu and Zhang 2006 ).”
- Sparse Additive Ordinary Differential Equations for Dynamic Gene Regulatory Network Modeling (2014, methodology): “Note that, if the longitudinally replicate data are available (see our application example in Section 5), the nonparametric mixed-effects smoothing methods can be used in this step to obtain better smoothing results (Wu and Zhang 2006; Lu et al. 2011).”