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Bayesian semiparametric regression in the presence of conditionally heteroscedastic measurement and regression errors

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  • Abhra Sarkar
  • Bani K. Mallick
  • Raymond J. Carroll

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  • Abhra Sarkar & Bani K. Mallick & Raymond J. Carroll, 2014. "Bayesian semiparametric regression in the presence of conditionally heteroscedastic measurement and regression errors," Biometrics, The International Biometric Society, vol. 70(4), pages 823-834, December.
  • Handle: RePEc:bla:biomet:v:70:y:2014:i:4:p:823-834
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    File URL: http://hdl.handle.net/10.1111/biom.12197
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    References listed on IDEAS

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    1. Delaigle, Aurore & Meister, Alexander, 2007. "Nonparametric Regression Estimation in the Heteroscedastic Errors-in-Variables Problem," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1416-1426, December.
    2. Wang, Xiao-Feng & Wang, Bin, 2011. "Deconvolution Estimation in Measurement Error Models: The R Package decon," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 39(i10).
    3. Susanne M. Schennach, 2004. "Estimation of Nonlinear Models with Measurement Error," Econometrica, Econometric Society, vol. 72(1), pages 33-75, January.
    4. Devanarayan, Viswanath & Stefanski, Leonard A., 2002. "Empirical simulation extrapolation for measurement error models with replicate measurements," Statistics & Probability Letters, Elsevier, vol. 59(3), pages 219-225, October.
    5. Pelenis, Justinas, 2014. "Bayesian regression with heteroscedastic error density and parametric mean function," Journal of Econometrics, Elsevier, vol. 178(P3), pages 624-638.
    6. Schennach, Susanne M., 2004. "Nonparametric Regression In The Presence Of Measurement Error," Econometric Theory, Cambridge University Press, vol. 20(6), pages 1046-1093, December.
    7. Staudenmayer, John & Ruppert, David & Buonaccorsi, John P., 2008. "Density Estimation in the Presence of Heteroscedastic Measurement Error," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 726-736, June.
    8. Raymond J. Carroll & Peter Hall, 2004. "Low order approximations in deconvolution and regression with errors in variables," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(1), pages 31-46, February.
    9. Raymond J. Carroll & Kathryn Roeder & Larry Wasserman, 1999. "Flexible Parametric Measurement Error Models," Biometrics, The International Biometric Society, vol. 55(1), pages 44-54, March.
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    Cited by:

    1. Sarah C. Lotspeich & Bryan E. Shepherd & Gustavo G. C. Amorim & Pamela A. Shaw & Ran Tao, 2022. "Efficient odds ratio estimation under two‐phase sampling using error‐prone data from a multi‐national HIV research cohort," Biometrics, The International Biometric Society, vol. 78(4), pages 1674-1685, December.
    2. Li, Mengyan & Ma, Yanyuan & Li, Runze, 2019. "Semiparametric regression for measurement error model with heteroscedastic error," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 320-338.

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