Equivalent Kernels of Smoothing Splines in Nonparametric Regression for Clustered/Longitudinal Data
By Xihong Lin, Naisyin Wang, Alan H. Welsh, Raymond J. Carroll. 2004
100 citations recorded by the source corpus.
Subfields: Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/7a38b4542ee2eb98f02e88c5c07791df9bde2a7f
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In Statistics and Probability
- Raymond J. Carroll
- Xihong Lin
- Jianhui Zhou
- Annie Qu
- Naisyin Wang
- Jeng-Min Chiou
- Randall Eubank
- Suojin Wang
Citations in the corpus
- Functional Regression (2014, unknown): “They mentioned that smoothing spline estimates of functional coefficients from correlated data are consistent but inefficient if the within-function correlation is ignored (Lin et al. 2004).”
- Informative Estimation and Selection of Correlation Structure for Longitudinal Data (2012, methodology): “…modeling correlation structure will increase the efficiency of the regression parameter estimator, increase statistical power for hypothesis testing, and reduce the bias of the estimator in nonparametric modeling for longitudinal data (Wang 2003; Lin et al. 2004; Wang, Carroll, and Lin 2005).”
- Efficient semiparametric estimator for heteroscedastic partially linear models (2006, background): “…equivalence between kernel- and spline-estimated g has been established for both uncorrelated data (Silverman, 1984; Nychka, 1995) and correlated data (Lin et al., 2004), without uniform equivalence results, it is nontrivial to establish rigorously equivalence between the ways of estimating b.”
- Smoothing spline estimation in varying‐coefficient models (2004, background): “…proceed as in the beginning of Section 2 and take (tij, zij, uTij/, j =1, . . . , ri, to be the observed data for the ith subject, i=1, . . . , R. Lin et al. (2004) considered a special case with k = 1 and u1ij ≡ 1 and showed that the one-step update smoothing spline estimator described above is…”
- Semiparametric estimation in general repeated measures problems (2006, background): “Then as Lin et al. (2004) showed, there is a smoother matrix S =S.Σ"/ such that θ̂.”