Testing structural change in partially linear single-index models with error-prone linear covariates

DOI10.1016/j.csda.2012.10.002zbMath1400.62095OpenAlexW2015777348MaRDI QIDQ1621211

Zhen Pang, Tao Hu, Zhen-Sheng Huang

Publication date: 8 November 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2012.10.002

zbMATH Keywords

chi-squared distributionsingle-index modellocal linear methodmeasure error\(F\)-type test

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Applications of statistics to biology and medical sciences; meta analysis (62P10) Parametric hypothesis testing (62F03)

Related Items (4)

Adaptive structure inferences on partially linear error-in-function models with error-prone covariates ⋮ Data-driven model checking for errors-in-variables varying-coefficient models with replicate measurements ⋮ Empirical-likelihood-based Test for Partially Linear Single-index Models with Error-prone Linear Covariates ⋮ Improved statistical inference on semiparametric varying-coefficient partially linear measurement error model

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• Generalized Partially Linear Single-Index Models
• Penalized Spline Estimation for Partially Linear Single-Index Models
• Local and Omnibus Goodness-of-Fit Tests in Classical Measurement Error Models
• Measurement Error in Nonlinear Models

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