IDEAS home Printed from https://ideas.repec.org/a/eee/jmvana/v102y2011i2p386-392.html
   My bibliography  Save this article

A multivariate ultrastructural errors-in-variables model with equation error

Author

Listed:
  • Patriota, Alexandre G.
  • Bolfarine, Heleno
  • Arellano-Valle, Reinaldo B.

Abstract

This paper deals with asymptotic results on a multivariate ultrastructural errors-in-variables regression model with equation errors. Sufficient conditions for attaining consistent estimators for model parameters are presented. Asymptotic distributions for the line regression estimators are derived. Applications to the elliptical class of distributions with two error assumptions are presented. The model generalizes previous results aimed at univariate scenarios.

Suggested Citation

  • Patriota, Alexandre G. & Bolfarine, Heleno & Arellano-Valle, Reinaldo B., 2011. "A multivariate ultrastructural errors-in-variables model with equation error," Journal of Multivariate Analysis, Elsevier, vol. 102(2), pages 386-392, February.
    • Handle: RePEc:eee:jmvana:v:102:y:2011:i:2:p:386-392
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0047-259X(10)00187-9
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Healy, John D., 1980. "Maximum likelihood estimation of a multivariate linear functional relationship," Journal of Multivariate Analysis, Elsevier, vol. 10(2), pages 243-251, June.
    2. H. Schneeweiß, 1976. "Consistent estimation of a regression with errors in the variables," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 23(1), pages 101-115, December.
    3. Dahm, P. Fred & Fuller, Wayne A., 1986. "Generalized least squares estimation of the functional multivariate linear errors-in-variables model," Journal of Multivariate Analysis, Elsevier, vol. 19(1), pages 132-141, 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. Cheng, C.-L. & Shalabh, & Garg, G., 2016. "Goodness of fit in restricted measurement error models," Journal of Multivariate Analysis, Elsevier, vol. 145(C), pages 101-116.

    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. Shalabh, 1998. "Improved Estimation in Measurement Error Models Through Stein Rule Procedure," Journal of Multivariate Analysis, Elsevier, vol. 67(1), pages 35-48, October.
    2. Jain, Kanchan & Singh, Sukhbir & Sharma, Suresh, 2011. "Restricted estimation in multivariate measurement error regression model," Journal of Multivariate Analysis, Elsevier, vol. 102(2), pages 264-280, February.
    3. Bai, Jushan, 2024. "Likelihood approach to dynamic panel models with interactive effects," Journal of Econometrics, Elsevier, vol. 240(1).
    4. Cheng, C.-L. & Shalabh, & Garg, G., 2014. "Coefficient of determination for multiple measurement error models," Journal of Multivariate Analysis, Elsevier, vol. 126(C), pages 137-152.
    5. Thiel, Hendrik & Thomsen, Stephan L., 2013. "Noncognitive skills in economics: Models, measurement, and empirical evidence," Research in Economics, Elsevier, vol. 67(2), pages 189-214.
    6. Albert Satorra, 1996. "Fusion of data sets in multivariate linear regression with errors-in-variables," Economics Working Papers 183, Department of Economics and Business, Universitat Pompeu Fabra.
    7. A. Saleh & Jan Picek & Jan Kalina, 2012. "R-estimation of the parameters of a multiple regression model with measurement errors," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 75(3), pages 311-328, April.
    8. Shalabh & Garg, Gaurav & Misra, Neeraj, 2007. "Restricted regression estimation in measurement error models," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 1149-1166, October.
    9. Kim, H.M. & Saleh, A.K.Md.Ehsanes, 2005. "Improved estimation of regression parameters in measurement error models," Journal of Multivariate Analysis, Elsevier, vol. 95(2), pages 273-300, August.
    10. Scott Gilbert & Petr Zemčík, 2005. "Testing for Latent Factors in Models with Autocorrelation and Heteroskedasticity of Unknown Form," Southern Economic Journal, John Wiley & Sons, vol. 72(1), pages 236-252, July.
    11. Liang, Hua & Song, Weixing, 2009. "Improved estimation in multiple linear regression models with measurement error and general constraint," Journal of Multivariate Analysis, Elsevier, vol. 100(4), pages 726-741, April.
    12. A. Ronner & A. Steerneman, 1985. "The occurrence of outliers in the explanatory variable considered in an errors-in-variables framework," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 32(1), pages 97-107, December.
    13. R. Ketellapper & A. Ronner, 1984. "Are robust estimation methods useful in the structural errors-in-variables model?," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 31(1), pages 33-41, December.
    14. Chris Tofallis, 2023. "Fitting an Equation to Data Impartially," Mathematics, MDPI, vol. 11(18), pages 1-14, September.
    15. Srivastava, Anil K. & Shalabh, 1997. "A new property of Stein procedure in measurement error model," Statistics & Probability Letters, Elsevier, vol. 32(3), pages 231-234, March.
    16. Cheng, C.-L. & Shalabh, & Garg, G., 2016. "Goodness of fit in restricted measurement error models," Journal of Multivariate Analysis, Elsevier, vol. 145(C), pages 101-116.
    17. Schneeweiss, H. & Shalabh, H., 2007. "On the estimation of the linear relation when the error variances are known," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 1143-1148, October.
    18. Chris Tofallis, 2024. "Fitting an Equation to Data Impartially," Papers 2409.02573, arXiv.org.
    19. Sukhbir Singh & Kanchan Jain & Suresh Sharma, 2014. "Replicated measurement error model under exact linear restrictions," Statistical Papers, Springer, vol. 55(2), pages 253-274, May.
    20. Guo, Meixi & Ghosh, Malay, 2012. "Mean squared error of James–Stein estimators for measurement error models," Statistics & Probability Letters, Elsevier, vol. 82(11), pages 2033-2043.

    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:eee:jmvana:v:102:y:2011:i:2:p:386-392. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    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.