Statistical tests in the partially linear additive regression models

DOI10.1016/j.stamet.2014.02.001zbMath1486.62098OpenAlexW1974967627MaRDI QIDQ1731204

Salim Bouzebda, Khalid Chokri

Publication date: 13 March 2019

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

Full work available at URL: https://doi.org/10.1016/j.stamet.2014.02.001

zbMATH Keywords

asymptotic normalityhypothesis testinglaw of iterated logarithmcurse of dimensionalitypartially linear modelsadditive modelkernel-type estimatorsmarginal integration

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Density estimation (62G07) Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20)

Related Items (1)

Uniform convergence rate of the kernel regression estimator adaptive to intrinsic dimension in presence of censored data

Uses Software

• KernSmooth

Cites Work

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• The existence and asymptotic properties of a backfitting projection algorithm under weak conditions
• Strong consistency of the internal estimator of nonparametric regression with dependent data
• Semi-parametric regression: efficiency gains from modeling the nonparametric part
• Linear smoothers and additive models
• On internally corrected and symmetrized kernel estimators for nonparametric regression
• Asymptotic results for the linear parameter estimate in partially linear additive regression model
• Robust likelihood inference for regression parameters in partially linear models
• The dimensionality reduction principle for generalized additive models
• Additive regression and other nonparametric models
• Convergence rates for partially splined models
• Convergence rates for parametric components in a partly linear model
• A two-stage spline smoothing method for partially linear models
• Series estimation of semilinear models
• Fitting a bivariate additive model by local polynomial regression
• Semiparametric inference in a partial linear model
• Local linear estimation in partly linear models
• A consistent test for heteroscedasticity in nonparametric regression based on the kernel method
• Direct estimation of low-dimensional components in additive models.
• Asymptotic normality of parametric part in partially linear models with measurement error in the nonparametric part
• On some global measures of the deviations of density function estimates
• Rate optimal estimation with the integration method in the presence of many covariates
• Uniform in bandwidth consistency of kernel-type function estimators
• Vers un test d'additivité en régression non paramétrique sous des conditions de mélange
• Testing heteroscedasticity in partially linear models with missing covariates
• Curve fitting by polynomial-trigonometric regression
• A consistent test for heteroscedasticity in semi-parametric regression with nonparametric variance function based on the kernel method
• Additive partial linear models with measurement errors
• A robust test for homoscedasticity in nonparametric regression
• Estimating Optimal Transformations for Multiple Regression and Correlation
• Root-N-Consistent Semiparametric Regression
• On higher order kernels
• Testing Heteroscedasticity In Nonparametric Regression
• Versions of Kernel-Type Regression Estimators
• Nonparametric Identification of Nonlinear Time Series: Projections
• A Comparison of Higher-Order Bias Kernel Density Estimators
• Testing homoscedasticity in nonparametric regression
• A Note on the Convergent Rates of M-Estimates for a Partly Linear Model
• A kernel method of estimating structured nonparametric regression based on marginal integration
• A simple bias reduction method for density estimation
• A note on kernel density estimation at a parametric rate†
• On Estimation of a Probability Density Function and Mode
• An empirical process approach to the uniform consistency of kernel-type function estimators
• Combinatorial methods in density estimation

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