Testing goodness of fit of polynomial models via spline smoothing techniques

DOI10.1016/0167-7152(94)90070-1zbMath0793.62026OpenAlexW2024217456MaRDI QIDQ1324591

Juei-Chao Chen

Publication date: 24 May 1994

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-7152(94)90070-1

zbMATH Keywords

local alternativesnonparametric regressionnull hypothesislarge sample propertiestesting goodness of fit\(2m\)-th order smoothing spline estimator\(m\)-th order derivative\(m\)-th order polynomial regression model

Mathematics Subject Classification ID

Density estimation (62G07) Nonparametric hypothesis testing (62G10) Asymptotic distribution theory in statistics (62E20) General nonlinear regression (62J02)

Related Items (6)

Assessing the equivalence of nonparametric regression tests based on spline and local polynomial smoothers ⋮ Data-driven rate-optimal specification testing in regression models ⋮ Local and global asymptotic inference in smoothing spline models ⋮ Smoothing-based lack-of-fit tests: variations on a theme ⋮ X²goodness-of-fit tests for polynomial regression ⋮ Testing for no effect via splines

Cites Work

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• Commonality of cusum, von Neumann and smoothing-based goodness-of-fit tests
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• Distribution of the Ratio of the Mean Square Successive Difference to the Variance

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