Using local linear kernel smoothers to test the lack of fit of nonlinear regression models

DOI10.1016/j.stamet.2005.06.001zbMath1248.62056OpenAlexW2006629703MaRDI QIDQ713661

Chin-Shang Li

Publication date: 19 October 2012

Published in: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.stamet.2005.06.001

zbMATH Keywords

boundary effectsbandwidth selectionfit comparisonslocal linear kernel estimator

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) General nonlinear regression (62J02)

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A computational validation for nonparametric assessment of spatial trends ⋮ An updated review of goodness-of-fit tests for regression models ⋮ A goodness-of-fit test for regression models with spatially correlated errors ⋮ Improved model checking methods for parametric models with responses missing at random ⋮ Testing for no effect via splines

Cites Work

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• An omnibus test for departures from constant mean
• Testing the (parametric) null model hypothesis in (semiparametric) partial and generalized spline models
• Comparing nonparametric versus parametric regression fits
• Two-sample test statistics for measuring discrepancies between two multivariate probability density functions using kernel-based density estimates
• Testing for affine equivalence of elliptically symmetric distributions.
• On the multivariate runs test
• Jackknife, bootstrap and other resampling methods in regression analysis
• Goodness-of-fit test for linear models based on local polynomials
• Testing the Goodness of Fit of a Linear Model Via Nonparametric Regression Techniques
• Smooth optimum kernel estimators near endpoints
• How Far Are Automatically Chosen Regression Smoothing Parameters From Their Optimum?
• Residual variance and residual pattern in nonlinear regression
• Nonparametric testing the similarity of two unknown density functions: local power and bootstrap analysis
• On goodness-of-fit tests for weakly dependent processes using kernel method
• Nonparametric statistics for testing of linearity and serial independence
• Smoothing-based lack-of-fit tests: variations on a theme
• An Adaptive, Rate-Optimal Test of a Parametric Mean-Regression Model Against a Nonparametric Alternative
• Nonparametric tests of linearity for time series
• On the Departure from Normality of a Certain Class of Martingales

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