Efficient Estimation and Inferences for Varying-Coefficient Models

By Zongwu Cai, Jianqing Fan, Runze Li. 2000

503 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/786adede4526872a1c5a90562277dde066a6e690

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In Statistics and Probability

Citations in the corpus

Estimation of the covariance matrix of random effects in longitudinal studies (2007, background): “There is a growing literature addressing this kind of model, which includes Hastie and Tibshirani [12], Xia and Li [29], Cai, Fan and Li [ 1 ], Zhang, Lee and Song [32], Fan, Yao and Cai [9] and the references therein.”
Adaptive varying‐coefficient linear models (2003, background): “…data analysis, Hoover et al. (1998), Wu et al. (1998) and Fan and J. Zhang (2000) on longitudinal data analysis, Nicholls and Quinn (1982), Chen and Tsay (1993) and Cai, Fan and Yao (2000) on non-linear time series and Cai, Fan and Li (2000) on generalized linear models with varying coefficients.”
On the Cox Model With Time-Varying Regression Coefficients (2005, methodology): “Models with varying regression coefficients other than the Cox model have been studied by, for example, Hastie and Tibshirani (1993), Cai, Fan, and Li (2000), Fan and Zhang (2000), and Huang, Wu, and Zhou (2002).”
Quantile regression with varying coefficients (2007, methodology): “Following [1, 2], we simulate the null distribution via the residual bootstrap.”
Variable selection for high-dimensional generalized varying-coefficient models (2012, background): “Of particular interests to us is the generalized varying-coefficient models (GVCM) (Hastie and Tibshirani (1993); Cai, Fan, and Li (2000)) in which the coefficients β in GLMs are replaced with smooth nonparametric functions that depends on an index variable T , resulting in g(E[Y |X,T ]) = g(µ) =…”
A UNIFIED VARIABLE SELECTION APPROACH FOR VARYING COEFFICIENT MODELS (2012, background): “…and constant coefficients (Huang, Wu, and Zhou (2002)); Wang, Zhu, and Zhou (2009)); (ii) selection of variables with nonzero varying coefficients (Cai, Fan, and Li (2000), Qu and Li (2006)); (iii) selection of variables with nonzero constant coefficients (Fan and Huang (2005), Wang, Zhu, and…”
Inference of time-varying regression models (2012, methodology): “The dataset has been studied by [7, 19, 20] by assuming that the observations are i.”
Nonparametric inference with generalized likelihood ratio tests (2007, background): “The generalized varying-coe‐cient models expand the scope of the applications from the normal-like of distributions to the exponential family of distributions, including the Binomial and Poisson distributions ( Cai, Fan and Li, 2000 ).”
Variable Selection in Semiparametric Regression Modeling. (2008, unknown): “BY RUNZE LI1 AND HUA LIANG2”
Shrinkage Estimation of the Varying Coefficient Model (2009, methodology): “Most existing research about the model focuses on either parameter estimation (Chen and Tsay 1993; Fan and Zhang 1999; Cai et al. 2000; Fan and Zhang 2000a; Huang, Wu, and Zhou 2002; Huang, Wu, and Zhou 2004; Fan and Huang 2005) or hypotheses testing (Fan and Zhang 2000b; Fan, Zhang, and Zhang…”
Efficient Estimation of Average Treatment Effects with Mixed Categorical and Continuous Data (2009, background): “Note that (2.6) can also be viewed as a functional coecient model (smooth coecient model) as considered by Chen and Tsay (1993), Cai, Fan and Yao (2000), Cai, Fan and Li (2000) , and Li et al. (2002), among others.”
Statistical Methods with Varying Coefficient Models. (2008, methodology): “Cai et al. (2000) showed the sandwich method worked quite well by extensive simulation studies.”
Simultaneous inference of linear models with time varying coefficients (2010, methodology): “In the context of varying-coefficient models, this data set has been studied by Fan and Zhang (1999, 2000) and Cai et al. (2000). Most of the previous results assumed that the observations were IID.”
ADAPTIVE SEMI-VARYING COEFFICIENT MODEL SELECTION (2012, methodology): “From (A.10) in the Appendix of Cai, Fan, and Li (2000), we obtain β̂ora(Zt)− β(Zt) = { n−1 n∑ i=1 q2{Xiβ(Zt), Yi}XiaX⊤iaKh(Zt − Zi) }−1 × { n−1 n∑ i=1 q1{Xiβ(Zt), Yi}XiaKh(Zt − Zi) } + op { (nh)−1/2 } .”
Statistical Estimation in Generalized Multiparameter Likelihood Models (2009, methodology): “The confidence bands were constructed using âj(·) ± 1.96SE, where SE is the standard error computed by a sandwich method (see Cai, Fan, and Li 2000).”