Smoothing-based lack-of-fit tests: variations on a theme

DOI10.1080/10485259608832685zbMath0877.62041OpenAlexW2049244250MaRDI QIDQ4349872

Maragatha Kuchibhatla, Jeffrey D. Hart

Publication date: 14 December 1997

Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10485259608832685

zbMATH Keywords

Fourier seriesnonparametric regressionparametric modelsautomated smoothing

Mathematics Subject Classification ID

Density estimation (62G07) Nonparametric hypothesis testing (62G10)

Related Items (12)

A note on variable selection in nonparametric regression with dependent data ⋮ Bootstrapping the order selection test ⋮ Goodness-of-fit test for nonparametric regression models: smoothing spline ANOVA models as example ⋮ A new nonparametric lack-of-fit test of nonlinear regression in presence of heteroscedastic variances ⋮ Goodness-of-fit test for monotonous nonlinear regression models. ⋮ Regional residual plots for assessing the fit of linear regression models ⋮ Using local linear kernel smoothers to test the lack of fit of nonlinear regression models ⋮ Frequentist-Bayes lack-of-fit tests based on Laplace approximations ⋮ An \(L_2\) error test with order selection and thresholding ⋮ A consistent test for the functional form of a regression based on a difference of variance estimators ⋮ Generalized likelihood ratio statistics and Wilks phenomenon ⋮ Model selection criteria with data dependent penalty, with applications to data-driven neyman smooth tests

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