Dimension-reduction type test for linearity of a stochastic regression model

DOI10.1007/BF02677423zbMath0927.62044OpenAlexW185917791MaRDI QIDQ1299826

Run-Ze Li, Li Xing Zhu

Publication date: 14 December 1999

Published in: Acta Mathematicae Applicatae Sinica. English Series (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02677423

zbMATH Keywords

kernel estimationprojection pursuittest of linearitynumber-theoretic method

Mathematics Subject Classification ID

Multivariate analysis (62H99) Nonparametric hypothesis testing (62G10) Linear regression; mixed models (62J05)

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An adaptive-to-model test for partially parametric single-index models, A minimum projected-distance test for parametric single-index Berkson models, A goodness-of-fit test for variable-adjusted models, Model checking for regressions: an approach bridging between local smoothing and global smoothing methods, Specification Testing of Regression Models with Mixed Discrete and Continuous Predictors, A Review on Dimension-Reduction Based Tests For Regressions, Breaking the curse of dimensionality in nonparametric testing, A robust adaptive-to-model enhancement test for parametric single-index models, Model checks for functional linear regression models based on projected empirical processes

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