IDEAS home Printed from https://ideas.repec.org/a/spr/testjl/v29y2020i2d10.1007_s11749-019-00662-6.html
   My bibliography  Save this article

Goodness-of-fit tests for censored regression based on artificial data points

Author

Listed:
  • Wenceslao González Manteiga

    (Universidade de Santiago de Compostela)

  • Cédric Heuchenne

    (HEC Liège, University of Liège
    Université catholique de Louvain)

  • César Sánchez Sellero

    (Universidade de Santiago de Compostela)

  • Alessandro Beretta

    (HEC Liège, University of Liège)

Abstract

Suppose we have a location-scale regression model where the location is the conditional mean and the scale is the conditional standard deviation; the response is possibly right-censored, the covariate is fully observed, and the error is independent of the covariate. We propose new goodness-of-fit testing procedures for the conditional mean and variance based on an integrated regression function technique which uses artificial data points. We obtain the weak convergence of the resulting processes and study their finite sample behavior via simulations. Finally, we analyze a data set about unemployment in Galicia.

Suggested Citation

  • Wenceslao González Manteiga & Cédric Heuchenne & César Sánchez Sellero & Alessandro Beretta, 2020. "Goodness-of-fit tests for censored regression based on artificial data points," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(2), pages 599-615, June.
  • Handle: RePEc:spr:testjl:v:29:y:2020:i:2:d:10.1007_s11749-019-00662-6
    DOI: 10.1007/s11749-019-00662-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11749-019-00662-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11749-019-00662-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Stute, W., 1993. "Consistent Estimation Under Random Censorship When Covariables Are Present," Journal of Multivariate Analysis, Elsevier, vol. 45(1), pages 89-103, April.
    2. Cédric Heuchenne & Ingrid Keilegom, 2010. "Estimation in nonparametric location-scale regression models with censored data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 62(3), pages 439-463, June.
    3. Heuchenne, Cedric & Van Keilegom, Ingrid, 2012. "Estimation of a general parametric location in censored regression," LIDAM Reprints ISBA 2012014, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    4. Holger Dette & Cedric Heuchenne, 2012. "Scale Checks in Censored Regression," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 39(2), pages 323-339, June.
    5. Cédric Heuchenne & Ingrid Keilegom, 2007. "Polynomial Regression with Censored Data based on Preliminary Nonparametric Estimation," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 59(2), pages 273-297, June.
    6. Heuchenne, C. & Van Keilegom, I., 2010. "Estimation in nonparametric location-scale regression models with censored data," LIDAM Reprints ISBA 2010015, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    7. Heuchenne, Cedric & Laurent, Geraldine, 2017. "Parametric conditional variance estimation in location-scale models with censored data," LIDAM Reprints ISBA 2017012, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sundarraman Subramanian, 2020. "Function-based hypothesis testing in censored two-sample location-scale models," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(1), pages 183-213, January.
    2. Lambert, Philippe, 2021. "Fast Bayesian inference using Laplace approximations in nonparametric double additive location-scale models with right- and interval-censored data," Computational Statistics & Data Analysis, Elsevier, vol. 161(C).
    3. Eoghan O'Neill, 2022. "Type I Tobit Bayesian Additive Regression Trees for Censored Outcome Regression," Papers 2211.07506, arXiv.org, revised Feb 2024.
    4. Sujica, Aleksandar & Van Keilegom, Ingrid, 2018. "The copula-graphic estimator in censored nonparametric location-scale regression models," Econometrics and Statistics, Elsevier, vol. 7(C), pages 89-114.
    5. García, A., 2016. "Oaxaca-Blinder Type Counterfactual Decomposition Methods for Duration Outcomes," Documentos de Trabajo 14186, Universidad del Rosario.
    6. 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.
    7. Zhiping Qiu & Jing Qin & Yong Zhou, 2016. "Composite Estimating Equation Method for the Accelerated Failure Time Model with Length-biased Sampling Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 396-415, June.
    8. Wang Zhu & Wang C.Y., 2010. "Buckley-James Boosting for Survival Analysis with High-Dimensional Biomarker Data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 9(1), pages 1-33, June.
    9. Lu, Xuewen, 2010. "Asymptotic distributions of two "synthetic data" estimators for censored single-index models," Journal of Multivariate Analysis, Elsevier, vol. 101(4), pages 999-1015, April.
    10. Ruoqing Zhu & Ying-Qi Zhao & Guanhua Chen & Shuangge Ma & Hongyu Zhao, 2017. "Greedy outcome weighted tree learning of optimal personalized treatment rules," Biometrics, The International Biometric Society, vol. 73(2), pages 391-400, June.
    11. Guessoum Zohra & Ould-Said Elias, 2009. "On nonparametric estimation of the regression function under random censorship model," Statistics & Risk Modeling, De Gruyter, vol. 26(3), pages 159-177, April.
    12. Weiyu Li & Valentin Patilea, 2018. "A dimension reduction approach for conditional Kaplan–Meier estimators," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(2), pages 295-315, June.
    13. Sungwan Bang & Soo-Heang Eo & Yong Mee Cho & Myoungshic Jhun & HyungJun Cho, 2016. "Non-crossing weighted kernel quantile regression with right censored data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 22(1), pages 100-121, January.
    14. Olivier Lopez & Xavier Milhaud & Pierre-Emmanuel Thérond, 2015. "Tree-based censored regression with applications to insurance," Working Papers hal-01141228, HAL.
    15. Cao, Yongxiu & Yu, Jichang, 2023. "Adjusting for unmeasured confounding in survival causal effect using validation data," Computational Statistics & Data Analysis, Elsevier, vol. 180(C).
    16. K. Hendrickx & P. Janssen & A. Verhasselt, 2018. "Penalized spline estimation in varying coefficient models with censored data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(4), pages 871-895, December.
    17. Mickaël De Backer & Anouar El Ghouch & Ingrid Van Keilegom, 2020. "Linear censored quantile regression: A novel minimum‐distance approach," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(4), pages 1275-1306, December.
    18. Amorim, Ana Paula & de Uña-Álvarez, Jacobo & Meira-Machado, Luís, 2011. "Presmoothing the transition probabilities in the illness-death model," Statistics & Probability Letters, Elsevier, vol. 81(7), pages 797-806, July.
    19. Uña-Álvarez, Jacobo de & González-Manteiga, Wenceslao, 1999. "Strong consistency under proportional censorship when covariables are present," Statistics & Probability Letters, Elsevier, vol. 42(3), pages 283-292, April.
    20. Feriel Bouhadjera & Mohamed Lemdani & Elias Ould Saïd, 2023. "Strong uniform consistency of the local linear relative error regression estimator under left truncation," Statistical Papers, Springer, vol. 64(2), pages 421-447, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:testjl:v:29:y:2020:i:2:d:10.1007_s11749-019-00662-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.