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A semi-parametric approach for mixture models: Application to local false discovery rate estimation

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  • Robin, Stephane
  • Bar-Hen, Avner
  • Daudin, Jean-Jacques
  • Pierre, Laurent
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    File URL: http://www.sciencedirect.com/science/article/B6V8V-4N7RW3X-1/2/0c325d5f9f1a5686a6ea57d934e49651
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    Bibliographic Info

    Article provided by Elsevier in its journal Computational Statistics & Data Analysis.

    Volume (Year): 51 (2007)
    Issue (Month): 12 (August)
    Pages: 5483-5493

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    Handle: RePEc:eee:csdana:v:51:y:2007:i:12:p:5483-5493

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    1. Allison, David B. & Gadbury, Gary L. & Heo, Moonseong & Fernandez, Jose R. & Lee, Cheol-Koo & Prolla, Tomas A. & Weindruch, Richard, 2002. "A mixture model approach for the analysis of microarray gene expression data," Computational Statistics & Data Analysis, Elsevier, vol. 39(1), pages 1-20, March.
    2. Paul Delmar & Stéphane Robin & Diana Tronik-Le Roux & Jean Jacques Daudin, 2005. "Mixture model on the variance for the differential analysis of gene expression data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(1), pages 31-50.
    3. Marco Di Marzio, 2004. "Boosting kernel density estimates: A bias reduction technique?," Biometrika, Biometrika Trust, vol. 91(1), pages 226-233, March.
    4. Efron B. & Tibshirani R. & Storey J.D. & Tusher V., 2001. "Empirical Bayes Analysis of a Microarray Experiment," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1151-1160, December.
    5. John D. Storey & Jonathan E. Taylor & David Siegmund, 2004. "Strong control, conservative point estimation and simultaneous conservative consistency of false discovery rates: a unified approach," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(1), pages 187-205.
    6. Efron, Bradley, 2004. "Large-Scale Simultaneous Hypothesis Testing: The Choice of a Null Hypothesis," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 96-104, January.
    7. Priebe, Carey E. & Marchette, David J., 2000. "Alternating kernel and mixture density estimates," Computational Statistics & Data Analysis, Elsevier, vol. 35(1), pages 43-65, November.
    8. Smyth Gordon K, 2004. "Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 3(1), pages 1-28, February.
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    Cited by:
    1. Friguet, Chloé & Causeur, David, 2011. "Estimation of the proportion of true null hypotheses in high-dimensional data under dependence," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2665-2676, September.
    2. Jaspers, Stijn & Aerts, Marc & Verbeke, Geert & Beloeil, Pierre-Alexandre, 2014. "A new semi-parametric mixture model for interval censored data, with applications in the field of antimicrobial resistance," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 30-42.
    3. Park, DoHwan & Park, Junyong & Zhong, Xiaosong & Sadelain, Michel, 2011. "Estimation of empirical null using a mixture of normals and its use in local false discovery rate," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2421-2432, July.
    4. Rostyslav Maiboroda & Olena Sugakova, 2012. "Nonparametric density estimation for symmetric distributions by contaminated data," Metrika, Springer, vol. 75(1), pages 109-126, January.

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