Nonparametric regression with errors in variables

By Jianqing Fan, Young Truong. 1993

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Citations in the corpus

Distribution-Free Distribution Regression (2013, methodology): “For comprehensive reviews and references, see Ramsay and Silverman [2005], Ferraty and Vieu [2006]. A popular approach to do machine learning, such as classification and regression, on the domain of distributions is to embed the distribution to a Hilbert space, introduce kernels between the distribu”
Nonlinear and Nonparametric Regression and Instrumental Variables (2004, methodology): “The deconvoluting kernel (Fan and Truong 1993, sec.”
Nonparametric Regression Estimation in the Heteroscedastic Errors-in-Variables Problem (2007, methodology): “We consider a weak version of consistency similar to that of Fan and Truong (1993).”
Asymptotic Normality of Parametric Part in Partially Linear Models with Measurement Error in the Nonparametric Part (2000, unknown): “The proof is mainly based upon the conclusion of Fan and Truong (1993). Lemma A.”
Instrumental Variable Estimation of Nonlinear Errors-in-Variables Models (2004, methodology): “…the characteristic function φ (ζ) of the disturbance u to be nonvanishing everywhere is a standard assumption in the deconvolution literature (Carroll, Ruppert, and Stefanski (1995), Fan (1991), Fan and Truong (1993), Li and Vuong (1998), Li (2002), Horowitz and Markatou (1996), Schennach (2004a)).”
A Bernstein-Von Mises Theorem for discrete probability distributions (2008, methodology): “Among the different approaches to non-parametric inference, using simple models with increasing dimensions has attracted attention in the context of maximum likelihood inference (Portnoy, 1988; Fan and Truong, 1993; Fan et al., 2001; Fan, 1993) and in the context of Bayesian inference (Ghosal, 2000)”
Gaussian Process Structural Equation Models with Latent Variables (2010, background): “Assumptions for the identiﬁability of functions f i ( · ) , given the identiﬁability of the joint of X , have been discussed in the literature of error-in-variables regression (Fan and Truong, 1993; Carroll et al., 2004).”
Bayesian Smoothing and Regression Splines for Measurement Error Problems (2002, methodology): “Fan and Truong (1993) showed that for additive normally distributed measurement error, the optimal rate of convergence is 8log4n592 for a globally consistent estimator when making no assumptions other than the existence of two continuous derivatives.”
Regression on manifolds: Estimation of the exterior derivative (2011, background): “Several formulations explicitly introduce noise into the model [11, 14, 28, 31, 41].”
Nonparametric covariate-adjusted regression (2016, methodology): “This contrasts with the errors-in-variables models studied by Fan and Truong (1993) and Delaigle et al. (2009), where convergence rates are significantly degraded by the measurement errors.”
A ridge-parameter approach to deconvolution (2007, methodology): “There is a large literature on kernel methods in this problem; see Fan and Truong [17] for theory and Carroll, Ruppert and Stefanski [5] for a survey.”
Local indirect least squares and average marginal effects in nonseparable structural systems (2012, methodology): “To obtain the rate for V; (z; h) = var(nLV; (z; h)), we impose bounds on the tail behavior of the Fourier transforms involved, as is common in the deconvolution literature (e.g. Fan, 1991; Fan and Truong, 1993).”