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A New Estimator of the Discovery Probability

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  • Stefano Favaro
  • Antonio Lijoi
  • Igor Prünster

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  • Stefano Favaro & Antonio Lijoi & Igor Prünster, 2012. "A New Estimator of the Discovery Probability," Biometrics, The International Biometric Society, vol. 68(4), pages 1188-1196, December.
    • Handle: RePEc:bla:biomet:v:68:y:2012:i:4:p:1188-1196
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2012.01793.x
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    References listed on IDEAS

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    1. Antonio Lijoi & Igor Pruenster & Stephen G. Walker, 2008. "Bayesian nonparametric estimators derived from conditional Gibbs structures," ICER Working Papers - Applied Mathematics Series 06-2008, ICER - International Centre for Economic Research.
    2. Chang Xuan Mao, 2004. "Predicting the Conditional Probability of Discovering a New Class," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 1108-1118, December.
    3. Jara, Alejandro & Hanson, Timothy & Quintana, Fernando A. & Müller, Peter & Rosner, Gary L., 2011. "DPpackage: Bayesian Semi- and Nonparametric Modeling in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i05).
    4. Stefano Favaro & Antonio Lijoi & Ramsés H. Mena & Igor Prünster, 2009. "Bayesian non‐parametric inference for species variety with a two‐parameter Poisson–Dirichlet process prior," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(5), pages 993-1008, November.
    5. Chang Xuan Mao, 2002. "A Poisson model for the coverage problem with a genomic application," Biometrika, Biometrika Trust, vol. 89(3), pages 669-682, August.
    6. Kolossiatis, M. & Griffin, J.E. & Steel, M.F.J., 2011. "Modeling overdispersion with the normalized tempered stable distribution," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2288-2301, July.
    7. Antonio Lijoi & Ramsés H. Mena & Igor Prünster, 2007. "Controlling the reinforcement in Bayesian non‐parametric mixture models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(4), pages 715-740, September.
    8. Antonio Lijoi & Ramsés H. Mena & Igor Prünster, 2007. "A Bayesian Nonparametric Method for Prediction in EST Analysis," ICER Working Papers - Applied Mathematics Series 16-2007, ICER - International Centre for Economic Research.
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    Cited by:

    1. Emanuele Dolera, 2022. "Asymptotic Efficiency of Point Estimators in Bayesian Predictive Inference," Mathematics, MDPI, vol. 10(7), pages 1-27, April.
    2. Roberto Fontana, 2015. "Optimal design generation: an approach based on discovery probability," Computational Statistics, Springer, vol. 30(4), pages 1231-1244, December.
    3. Cesari, Oriana & Favaro, Stefano & Nipoti, Bernardo, 2014. "Posterior analysis of rare variants in Gibbs-type species sampling models," Journal of Multivariate Analysis, Elsevier, vol. 131(C), pages 79-98.
    4. Julyan Arbel & Stefano Favaro, 2021. "Approximating Predictive Probabilities of Gibbs-Type Priors," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(1), pages 496-519, February.
    5. Antonio Canale & Igor Prünster, 2017. "Robustifying Bayesian nonparametric mixtures for count data," Biometrics, The International Biometric Society, vol. 73(1), pages 174-184, March.

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