Nonparametric Inferences for Additive Models

By Jianqing Fan, Jiancheng Jiang. 2005

175 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/867c176b03d3c17ecb5b8f7df4decfc1b2655339

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In Statistics and Probability

Citations in the corpus

Nonparametric inference with generalized likelihood ratio tests (2007, methodology): “Some additional references can be found in Fan and Jiang (2005) and Jiang et al (2007).”
FWDselect : Variable selection algorithm in regression models (2013, unknown): “…of variables are relevant, it would be possible to apply a likelihood ratio test (Neyman and Pearson, 1928) or a F-test type (Seber and Wild, 1989; Seber, 1997) in a parametric framework, or a generalized likelihood ratio test (Fan et al., 2001; Fan and Jiang, 2005, 2007) in a nonparametric one.”
Statistical testing of covariate effects in conditional copula models (2013, methodology): “, 2001), spectral density (Fan and Zhang, 2004), additive models (Fan and Jiang, 2005) and single-index models (Zhang et al.”
Statistical Estimation in Generalized Multiparameter Likelihood Models (2009, background): “…1993; Xia and Li 1999; Fan and Huang 2005; Cai et al. 2008; Li and Liang 2008), partially linear models (Engle et al. 1986; Härdle, Liang, and Gao 2000; Cai et al. 2007) and additive models (Hastie and Tibshirani 1990; Fan, Härdle, and Mammen 1998; Fan and Jiang 2005; Jiang and Zhou 2007).”
Spline-backfitted kernel smoothing of nonlinear additive autoregression model (2006, methodology): “Second, since our pilot spline estimator is thousands of times faster than the pilot kernel estimator in [15], our proposed method is computationally expedient; see Table 2.”
Sparse additive models (2007, methodology): “For example, the tests in Fan and Jiang (2005) could be used.”
An updated review of Goodness-of-Fit tests for regression models (2013, background): “From the former work by Eubank et al. (1995), there has been an extensive literature on tests for H0AM in (20), such as the contributions by Dette and von Lieres und Wilkau (2001), Gozalo and Linton (2001), Härdle et al. (2001), Derbort et al. (2002), and Fan and Jiang (2005).”
Nonparametric Independence Screening in Sparse Ultra-High Dimensional Additive Models (2009, methodology): “Given that in this work the additive components are specifically approximated by truncated series expansions with Bspline bases, the theoretical results should hold in general, and the proposed framework can be readily adapted to other smoothing methods with additive models (Silverman 1984; Horowitz”