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Smoothing the non-parametric estimate of a prior distribution by roughening : A computational study

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  • Laird, Nan M.
  • Louis, Thomas A.

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  • Laird, Nan M. & Louis, Thomas A., 1991. "Smoothing the non-parametric estimate of a prior distribution by roughening : A computational study," Computational Statistics & Data Analysis, Elsevier, vol. 12(1), pages 27-37, August.
    • Handle: RePEc:eee:csdana:v:12:y:1991:i:1:p:27-37
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    Cited by:

    1. Goutis, Constantinos, 1996. "Nonparametric estimation of a mixing density via the kernel method," DES - Working Papers. Statistics and Econometrics. WS 10437, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Pan, Wei & Louis, Thomas A., 1999. "Two semi-parametric empirical Bayes estimators," Computational Statistics & Data Analysis, Elsevier, vol. 30(2), pages 185-196, April.
    3. Chung, Yeojin & Lindsay, Bruce G., 2015. "Convergence of the EM algorithm for continuous mixing distributions," Statistics & Probability Letters, Elsevier, vol. 96(C), pages 190-195.
    4. M. M. Shoukri & M. Attanasio & J. M. Sargeant, 1998. "Parametric versus semi-parametric models for the analysis of correlated survival data: A case study in veterinary epidemiology," Journal of Applied Statistics, Taylor & Francis Journals, vol. 25(3), pages 357-374.
    5. Paddock, Susan M. & Ridgeway, Greg & Lin, Rongheng & Louis, Thomas A., 2006. "Flexible distributions for triple-goal estimates in two-stage hierarchical models," Computational Statistics & Data Analysis, Elsevier, vol. 50(11), pages 3243-3262, July.
    6. Brentnall, Adam R. & Crowder, Martin J. & Hand, David J., 2011. "Approximate repeated-measures shrinkage," Computational Statistics & Data Analysis, Elsevier, vol. 55(2), pages 1150-1159, February.

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