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Smooth Residual Bootstrap for Empirical Processes of Non‐parametric Regression Residuals

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  • NATALIE NEUMEYER

Abstract

. The aim of this paper is to prove the validity of smooth residual bootstrap versions of procedures that are based on the empirical process of residuals estimated from a non‐parametric regression model. From this result, consistency of various model tests in non‐parametric regression is deduced, such as goodness‐of‐fit tests for the regression and variance function, tests for equality of regression functions and tests concerning the error distribution.

Suggested Citation

  • Natalie Neumeyer, 2009. "Smooth Residual Bootstrap for Empirical Processes of Non‐parametric Regression Residuals," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(2), pages 204-228, June.
    • Handle: RePEc:bla:scjsta:v:36:y:2009:i:2:p:204-228
    DOI: 10.1111/j.1467-9469.2008.00628.x
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    References listed on IDEAS

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    1. Ingrid Keilegom & Wenceslao González Manteiga & César Sánchez Sellero, 2008. "Goodness-of-fit tests in parametric regression based on the estimation of the error distribution," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 17(2), pages 401-415, August.
    2. Cheng, Fuxia, 2002. "Consistency of error density and distribution function estimators in nonparametric regression," Statistics & Probability Letters, Elsevier, vol. 59(3), pages 257-270, October.
    3. Mora, Juan & Neumeyer, Natalie, 2005. "The Two-Sample Problem with Regression Errors : An Empirical Process Approach," Technical Reports 2005,05, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    4. Anton Schick & Wolfgang Wefelmeyer, 2002. "Estimating the Innovation Distribution in Nonlinear Autoregressive Models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 54(2), pages 245-260, June.
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    6. Koul, H. L. & Lahiri, S. N., 1994. "On Bootstrapping M-Estimated Residual Processes in Multiple Linear-Regression Models," Journal of Multivariate Analysis, Elsevier, vol. 49(2), pages 255-265, May.
    7. Michael G. Akritas & Ingrid Van Keilegom, 2001. "Non‐parametric Estimation of the Residual Distribution," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 28(3), pages 549-567, September.
    8. Natalie Neumeyer, 2008. "A bootstrap version of the residual-based smooth empirical distribution function," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 20(2), pages 153-174.
    9. Holger Dette & Natalie Neumeyer & Ingrid Van Keilegom, 2007. "A new test for the parametric form of the variance function in non‐parametric regression," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(5), pages 903-917, November.
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    Cited by:

    1. Colling, Benjamin & Van Keilegom, Ingrid, 2016. "Goodness-of-fit tests in semiparametric transformation models using the integrated regression function," LIDAM Discussion Papers ISBA 2016031, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    2. Hušková, Marie & Meintanis, Simos G. & Pretorius, Charl, 2020. "Tests for validity of the semiparametric heteroskedastic transformation model," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
    3. Jun Zhang & Zhenghui Feng & Xiaoguang Wang, 2018. "A constructive hypothesis test for the single-index models with two groups," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 70(5), pages 1077-1114, October.
    4. Hotta, Luiz & Trucíos, Carlos & Ruiz Ortega, Esther, 2015. "Robust bootstrap forecast densities for GARCH models: returns, volatilities and value-at-risk," DES - Working Papers. Statistics and Econometrics. WS ws1523, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. Chen Zhong, 2025. "Simultaneous inference and trend specification testing in ARMA model with trend via innovation distribution function," Statistical Papers, Springer, vol. 66(5), pages 1-24, August.
    6. Florens, Jean-Pierre & Simar, Léopold & Van Keilegom, Ingrid, 2014. "Frontier estimation in nonparametric location-scale models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 456-470.
    7. Tan, Falong & Guo, Xu & Zhu, Lixing, 2025. "Weighted residual empirical processes, martingale transformations, and model specification tests for regressions with diverging number of parameters," Journal of Econometrics, Elsevier, vol. 252(PA).
    8. Feve, Frederique & Florens, Jean-Pierre & Van Keilegom, Ingrid, 2012. "Estimation of conditional ranks and tests of exogeneity in nonparametric nonseparable models," LIDAM Discussion Papers ISBA 2012036, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    9. Pardo-Fernandez, Juan Carlos & Jimenez-Gamero, Maria Dolores & El Ghouch, Anouar, 2013. "A nonparametric ANOVA-type test for regression curves based on characteristic functions," LIDAM Discussion Papers ISBA 2013022, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    10. Wenceslao González-Manteiga & Rosa Crujeiras, 2013. "An updated review of Goodness-of-Fit tests for regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 361-411, September.
    11. Gu, Lijie & Wang, Suojin & Yang, Lijian, 2021. "Smooth simultaneous confidence band for the error distribution function in nonparametric regression," Computational Statistics & Data Analysis, Elsevier, vol. 155(C).
    12. Colling, Benjamin & Van Keilegom, Ingrid, 2017. "Goodness-of-fit tests in semiparametric transformation models using the integrated regression function," Journal of Multivariate Analysis, Elsevier, vol. 160(C), pages 10-30.
    13. Neumeyer, Natalie & Van Keilegom, Ingrid, 2010. "Estimating the error distribution in nonparametric multiple regression with applications to model testing," Journal of Multivariate Analysis, Elsevier, vol. 101(5), pages 1067-1078, May.
    14. Juan Carlos Pardo-Fernández & María Dolores Jiménez-Gamero & Anouar El Ghouch, 2015. "A Non-parametric ANOVA-type Test for Regression Curves Based on Characteristic Functions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 197-213, March.
    15. Hu, Yue & Li, Haiqi & Tan, Falong, 2024. "Testing the parametric form of the conditional variance in regressions based on distance covariance," Computational Statistics & Data Analysis, Elsevier, vol. 189(C).
    16. Neumeyer, Natalie & Noh, Hohsuk & Van Keilegom, Ingrid, 2014. "Heteroscedastic semiparametric transformation models: estimation and testing for validity," LIDAM Discussion Papers ISBA 2014047, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    17. Heuchenne, Cédric & Van Keilegom, Ingrid, 2010. "Goodness-of-fit tests for the error distribution in nonparametric regression," Computational Statistics & Data Analysis, Elsevier, vol. 54(8), pages 1942-1951, August.
    18. Holger Dette & Juan Carlos Pardo‐Fernández & Ingrid Van Keilegom, 2009. "Goodness‐of‐Fit Tests for Multiplicative Models with Dependent Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(4), pages 782-799, December.
    19. Melanie Birke & Natalie Neumeyer, 2013. "Testing Monotonicity of Regression Functions – An Empirical Process Approach," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(3), pages 438-454, September.
    20. Cédric Heuchenne & Juan Pardo-Fernández, 2012. "Testing for one-sided alternatives in nonparametric censored regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 498-518, September.

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