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Density Estimation in the Presence of Heteroscedastic Measurement Error

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  • Staudenmayer, John
  • Ruppert, David
  • Buonaccorsi, John P.

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  • 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.
    • Handle: RePEc:bes:jnlasa:v:103:y:2008:m:june:p:726-736
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    1. Murray Aitkin, 1999. "A General Maximum Likelihood Analysis of Variance Components in Generalized Linear Models," Biometrics, The International Biometric Society, vol. 55(1), pages 117-128, March.
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    3. Jullion, Astrid & Lambert, Philippe, 2007. "Robust specification of the roughness penalty prior distribution in spatially adaptive Bayesian P-splines models," Computational Statistics & Data Analysis, Elsevier, vol. 51(5), pages 2542-2558, February.
    4. Schennach, Susanne M., 2004. "Nonparametric Regression In The Presence Of Measurement Error," Econometric Theory, Cambridge University Press, vol. 20(6), pages 1046-1093, December.
    5. R. DerSimonian, 1986. "Maximum Likelihood Estimation of a Mixing Distribution," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 35(3), pages 302-309, November.
    6. A. Delaigle & I. Gijbels, 2002. "Estimation of integrated squared density derivatives from a contaminated sample," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 869-886, October.
    7. 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.
    8. Daowen Zhang & Marie Davidian, 2001. "Linear Mixed Models with Flexible Distributions of Random Effects for Longitudinal Data," Biometrics, The International Biometric Society, vol. 57(3), pages 795-802, September.
    9. Carriquiry, Alicia L. & Fuller, Wayne A., 1996. "A Semiparametric Approach to Estimating Usual Intake Distributions," Staff General Research Papers Archive 1036, Iowa State University, Department of Economics.
    10. Wendimagegn Ghidey & Emmanuel Lesaffre & Paul Eilers, 2004. "Smooth Random Effects Distribution in a Linear Mixed Model," Biometrics, The International Biometric Society, vol. 60(4), pages 945-953, December.
    11. 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.
    12. Aurore Delaigle & Peter Hall & Peihua Qiu, 2006. "Nonparametric methods for solving the Berkson errors‐in‐variables problem," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(2), pages 201-220, April.
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    1. 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.
    2. Delaigle, Aurore & Fan, Jianqing & Carroll, Raymond J., 2009. "A Design-Adaptive Local Polynomial Estimator for the Errors-in-Variables Problem," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 348-359.
    3. DongHyuk Lee & Soumendra N. Lahiri & Samiran Sinha, 2020. "A test of homogeneity of distributions when observations are subject to measurement errors," Biometrics, The International Biometric Society, vol. 76(3), pages 821-833, September.
    4. 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.
    5. Roy, Arkaprava & Sarkar, Abhra, 2023. "Bayesian semiparametric multivariate density deconvolution via stochastic rotation of replicates," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
    6. Yousri Slaoui, 2021. "Data-driven Deconvolution Recursive Kernel Density Estimators Defined by Stochastic Approximation Method," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(1), pages 312-352, February.
    7. Zeng, Xiaochen & Wang, Jinru, 2018. "Wavelet density deconvolution estimations with heteroscedastic measurement errors," Statistics & Probability Letters, Elsevier, vol. 134(C), pages 79-85.
    8. Zhang Saijuan & Krebs-Smith Susan M. & Midthune Douglas & Perez Adriana & Buckman Dennis W. & Kipnis Victor & Freedman Laurence S. & Dodd Kevin W. & Carroll Raymond J, 2011. "Fitting a Bivariate Measurement Error Model for Episodically Consumed Dietary Components," The International Journal of Biostatistics, De Gruyter, vol. 7(1), pages 1-32, January.
    9. Julie McIntyre & Ronald P. Barry, 2012. "Bivariate deconvolution with SIMEX: an application to mapping Alaska earthquake density," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(2), pages 297-308, April.
    10. Wang, Xiao-Feng & Fan, Zhaozhi & Wang, Bin, 2010. "Estimating smooth distribution function in the presence of heteroscedastic measurement errors," Computational Statistics & Data Analysis, Elsevier, vol. 54(1), pages 25-36, January.
    11. 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.
    12. Mynbaev, Kairat & Martins-Filho, Carlos, 2015. "Consistency and asymptotic normality for a nonparametric prediction under measurement errors," Journal of Multivariate Analysis, Elsevier, vol. 139(C), pages 166-188.

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