IDEAS home Printed from https://ideas.repec.org/a/spr/aistmt/v55y2003i1p21-39.html
   My bibliography  Save this article

Estimation of partial linear error-in-response models with validation data

Author

Listed:
  • Qi-Hua Wang

Abstract

No abstract is available for this item.

Suggested Citation

  • Qi-Hua Wang, 2003. "Estimation of partial linear error-in-response models with validation data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 55(1), pages 21-39, March.
  • Handle: RePEc:spr:aistmt:v:55:y:2003:i:1:p:21-39
    DOI: 10.1007/BF02530483
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/BF02530483
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/BF02530483?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. Rice, John, 1986. "Convergence rates for partially splined models," Statistics & Probability Letters, Elsevier, vol. 4(4), pages 203-208, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wangli Xu & Lixing Zhu, 2015. "Nonparametric check for partial linear errors-in-covariables models with validation data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(4), pages 793-815, August.

    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. Guang Cheng & Hao Zhang & Zuofeng Shang, 2015. "Sparse and efficient estimation for partial spline models with increasing dimension," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(1), pages 93-127, February.
    2. Atak, Alev & Linton, Oliver & Xiao, Zhijie, 2011. "A semiparametric panel model for unbalanced data with application to climate change in the United Kingdom," Journal of Econometrics, Elsevier, vol. 164(1), pages 92-115, September.
    3. Emiko Dupont & Simon N. Wood & Nicole H. Augustin, 2022. "Spatial+: A novel approach to spatial confounding," Biometrics, The International Biometric Society, vol. 78(4), pages 1279-1290, December.
    4. Linton, Oliver, 1995. "Second Order Approximation in the Partially Linear Regression Model," Econometrica, Econometric Society, vol. 63(5), pages 1079-1112, September.
    5. Wang Q. & Linton O. & Hardle W., 2004. "Semiparametric Regression Analysis With Missing Response at Random," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 334-345, January.
    6. Han Shang, 2014. "Bayesian bandwidth estimation for a semi-functional partial linear regression model with unknown error density," Computational Statistics, Springer, vol. 29(3), pages 829-848, June.
    7. Wong, Heung & Liu, Feng & Chen, Min & Ip, Wai Cheung, 2009. "Empirical likelihood based diagnostics for heteroscedasticity in partial linear models," Computational Statistics & Data Analysis, Elsevier, vol. 53(9), pages 3466-3477, July.
    8. Qingming Zou & Zhongyi Zhu, 2014. "M-estimators for single-index model using B-spline," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 77(2), pages 225-246, February.
    9. Roger D. Peng & Francesca Dominici & Thomas A. Louis, 2006. "Model choice in time series studies of air pollution and mortality," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(2), pages 179-203, March.
    10. Boente, Graciela & Rodriguez, Daniela, 2008. "Robust bandwidth selection in semiparametric partly linear regression models: Monte Carlo study and influential analysis," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2808-2828, January.
    11. Schick, Anton, 1996. "Root-n consistent estimation in partly linear regression models," Statistics & Probability Letters, Elsevier, vol. 28(4), pages 353-358, August.
    12. Ibacache-Pulgar, Germán & Paula, Gilberto A., 2011. "Local influence for Student-t partially linear models," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1462-1478, March.
    13. Li, Chenxi, 2016. "Cause-specific hazard regression for competing risks data under interval censoring and left truncation," Computational Statistics & Data Analysis, Elsevier, vol. 104(C), pages 197-208.
    14. Hardle, Wolfgang & LIang, Hua & Gao, Jiti, 2000. "Partially linear models," MPRA Paper 39562, University Library of Munich, Germany, revised 01 Sep 2000.
    15. Golubev, Georgi & Härdle, Wolfgang, 1997. "On adaptive estimation in partial linear models," SFB 373 Discussion Papers 1997,100, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    16. Gao, Jiti & Liang, Hua, 1995. "Asymptotic normality of pseudo-LS estimator for partly linear autoregression models," Statistics & Probability Letters, Elsevier, vol. 23(1), pages 27-34, April.
    17. Baccini, Michela & Biggeri, Annibale & Lagazio, Corrado & Lertxundi, Aitana & Saez, Marc, 2007. "Parametric and semi-parametric approaches in the analysis of short-term effects of air pollution on health," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4324-4336, May.
    18. Wang, Jia & Cai, Xizhen & Li, Runze, 2021. "Variable selection for partially linear models via Bayesian subset modeling with diffusing prior," Journal of Multivariate Analysis, Elsevier, vol. 183(C).
    19. Germán Aneiros-Pérez, 2004. "Plug-in bandwidth choice for estimation of nonparametric part in partial linear regression models with strong mixing errors," Statistical Papers, Springer, vol. 45(2), pages 191-210, April.
    20. Häggström, Jenny, 2013. "Bandwidth selection for backfitting estimation of semiparametric additive models: A simulation study," Computational Statistics & Data Analysis, Elsevier, vol. 62(C), pages 136-148.

    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:aistmt:v:55:y:2003:i:1:p:21-39. 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.