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Stochastic restricted estimation in partially linear additive errors-in-variables models

Author

Listed:
  • Chuanhua Wei

    (Minzu University of China)

  • Jin Yang

    (The Hong Kong Polytechnic University)

Abstract

As a generalization of additive model and partially linear model, partially linear additive model has been paid considerably attention in recent years. This paper considers estimation of the parametric component of the semiparametric model when the covariates in the linear part are measured with additive error and some additional stochastic linear restrictions on the parametric component are available. Based on the corrected profile least-squares approach and mixed regression estimation method, we propose a corrected profile mixed estimator for the parametric component, and derive its asymptotic distribution. Finally, some simulation studies are conducted to illustrate the proposed procedure and the results are satisfactory.

Suggested Citation

  • Chuanhua Wei & Jin Yang, 2020. "Stochastic restricted estimation in partially linear additive errors-in-variables models," Statistical Papers, Springer, vol. 61(3), pages 1269-1279, June.
    • Handle: RePEc:spr:stpapr:v:61:y:2020:i:3:d:10.1007_s00362-018-0978-0
    DOI: 10.1007/s00362-018-0978-0
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    References listed on IDEAS

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    1. Chuan-hua Wei & Chunling Liu, 2012. "Statistical inference on semi-parametric partial linear additive models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(4), pages 809-823, December.
    2. Liang Li & Tom Greene, 2008. "Varying Coefficients Model with Measurement Error," Biometrics, The International Biometric Society, vol. 64(2), pages 519-526, June.
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    4. You, Jinhong & Chen, Gemai, 2006. "Estimation of a semiparametric varying-coefficient partially linear errors-in-variables model," Journal of Multivariate Analysis, Elsevier, vol. 97(2), pages 324-341, February.
    5. Wang, Qihua, 1999. "Estimation of Partial Linear Error-in-Variables Models with Validation Data," Journal of Multivariate Analysis, Elsevier, vol. 69(1), pages 30-64, April.
    6. Chuanhua Wei & Qihua Wang, 2012. "Statistical inference on restricted partially linear additive errors-in-variables models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(4), pages 757-774, December.
    7. Shalabh & Gaurav Garg & Neeraj Misra, 2010. "Consistent estimation of regression coefficients in ultrastructural measurement error model using stochastic prior information," Statistical Papers, Springer, vol. 51(3), pages 717-748, September.
    8. Chuanhua Wei & Yubo Luo & Xizhi Wu, 2012. "Empirical likelihood for partially linear additive errors-in-variables models," Statistical Papers, Springer, vol. 53(2), pages 485-496, May.
    9. Li, Qi, 2000. "Efficient Estimation of Additive Partially Linear Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 41(4), pages 1073-1092, November.
    10. Manzan, Sebastiano & Zerom, Dawit, 2005. "Kernel estimation of a partially linear additive model," Statistics & Probability Letters, Elsevier, vol. 72(4), pages 313-322, May.
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    Cited by:

    1. Jorge I. Figueroa-Zúñiga & Cristian L. Bayes & Víctor Leiva & Shuangzhe Liu, 2022. "Robust beta regression modeling with errors-in-variables: a Bayesian approach and numerical applications," Statistical Papers, Springer, vol. 63(3), pages 919-942, June.

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