Functional-Coefficient Regression Models for Nonlinear Time Series

By Zongwu Cai, Jianqing Fan, Qiwei Yao. 2000

652 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/69b53e4df1429b5d4cc595e7d658329032d31252

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Citations in the corpus

Convolutional autoregressive models for functional time series (2016, neutral): “Nonparametricmethods,suchassplinemethods(Silverman,1984; Brumback and Rice, 1998; Zhou et al., 1998; Cai et al., 2000) and kernel smoothing (Nadaraya, 1964; Watson, 1964; Fan and Gijbels, 1996), were often implemented to analyze functional data.”
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.”
Estimation and Testing for Varying Coefficients in Additive Models With Marginal Integration (2006, methodology): “The latter is different from Model I and was fully discussed by Cai, Fan, and Li (2000a) and Cai, Fan, and Yao (2000b) .”
NONPARAMETRIC ESTIMATION OF VARYING COEFFICIENT DYNAMIC PANEL DATA MODELS (2008, methodology): “We propose a nonparamet ric generalized method of moments (NPGMM) approach that is a combination of the local linear fitting of Fan and Gijbels (1996) and the generalized method of moments (GMM) approach of Hansen (1982).”
Trending time-varying coefficient time series models with serially correlated errors (2007, background): “where ajðt;cÞ is a given family of functions indexed by an unknown parameter vector c. Some tests similar to (9) have been considered in the econometrics and statistics literature; see Fan et al. (2001), Cai et al., 2000, Hong and Lee (2003), Cai and Tiwari (2000), Cai (2002), Kim (2001), and Juhl”
Partially linear hazard regression with varying coefficients for multivariate survival data (2008, methodology): “The model also is linked with the Cox model in the univariate case because of its semiparametric structures. It has received much attention in the literature. See for example, Wei et al. (1989), Lee et al.”
Local Linear GMM Estimation of Functional Coefficient IV Models With an Application to Estimating the Rate of Return to Schooling (2013, background): “…of the above issues, in recent years, the nonparametric varying/functional coefficient models have been considered by various authors, including Cleveland, Grosse, and Shyu (1992), Chen and Tsay (1993), Hastie and Tibshirani (1993), Fan and Zhang (1999), and Cai, Fan, and Yao (2000), among others.”
An analysis of global warming in the Alpine region based on nonlinear nonstationary time series models (2012, methodology): “A non parametric alternative, where the autoregressive coefficients are functions of the driving variable, was proposed by Chen and Tsay (1993), Cai et al.”
25 years of time series forecasting (2006, background): “The approach assumes little prior information on model structure without suffering from the “curse of dimensionality”; see also Cai et al. (2000).”
Efficient Estimation of Average Treatment Effects with Mixed Categorical and Continuous Data (2009, background): “Note that (4) can also be viewed as a functional coefficient model (i.e., a smooth coefficient model), which has been considered by a number of authors including Chen and Tsay (1993), Cai, Fan, and Yao (2000), Cai, Fan, and Li (2000), and Li et al. (2002).”