Goodness-of-Fit Tests for Parametric Regression Models

By Jianqing Fan, Li‐Shan Huang. 2001

160 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/0e2d222994fdf3223d78fe110d199f28d43b72cd

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Statistics and Probability

Citations in the corpus

An Adaptive, Rate-Optimal Test of Linearity for Median Regression Models (2002, background): “See, for example , Ait-Sahalia, et al . (1994) , Andrews”
Nonparametric Inferences for Additive Models (2005, methodology): “Fan and Huang (2001) proposed various testing techniques based on the adaptive Neyman test for various alternative models in the multiple regression setting.”
A Lack-of-Fit Test for Quantile Regression (2003, methodology): “We also made comparisons with an adaptive Neyman test of Fan and Huang (2001), who reported that the test was powerful in detecting nonparametric deviations to a parametric model with Gaussian errors.”
An Automatic Portmanteau Test for Serial Correlation (2009, methodology): “Fan and Huang (2001) considered data-driven Neyman s tests using Fourier transforms for linear models with independent and identically distributed (henceforth, iid) observations and Gaussian errors, extending Fan (1996) to the regression framework.”
Checking the adequacy of a partial linear model (2003, methodology): “Usually a normalizing constant is needed, say the estimator of the limiting variance, when the limiting null distribution of the test is used for p-values, Fan and Li (1996) and Fan and Huang (2001).”
New Estimation and Model Selection Procedures for Semiparametric Modeling in Longitudinal Data Analysis (2004, methodology): “To avoid the forementioned two problems, unbounded loss of efficiency and nonnegligible biases due to approximations, and to maintain the simplicity of Lin and Ying’s approach, we propose the following simple method from the partial linear model ( Fan and Huang 2001 ).”
Profile likelihood inferences on semiparametric varying-coefficient partially linear models (2005, methodology): “This kind of idea appears independently in the work of Yatchew (1997), who used ª0 ¼ ª1 ¼ 0, and Fan and Huang (2001), who used the linear terms to gain a better approximation.”
Model Checks Using Residual Marked Empirical Processes (2004, unknown): “…and Härdle (1994), Hong and White (1995), Fan and Li (1996), Zheng (1996), Stute (1997), Stute, Thies and Zhu (1998), Li and Wang (1998), Fan and Huang (2001), Horowitz and Spokoiny (2001), Li, Hsiao and Zinn (2003), Zhu (2003), Zhu and Ng (2003), Khmaladze and Koul (2004), Koul and Ni…”
Nonparametric inference with generalized likelihood ratio tests (2007, background): “For the regression problems, Fan (1996), Spokoiny (1996), Fan and Huang (2001) , Horowitz and Spokoiny (2001, 2002) established the adaptive optimality results.”
A difference based approach to the semiparametric partial linear model (2011, unknown): “semiparametric partial linear model”