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Estimating and Projecting Trends in HIV/AIDS Generalized Epidemics Using Incremental Mixture Importance Sampling

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  • Adrian E. Raftery
  • Le Bao

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  • Adrian E. Raftery & Le Bao, 2010. "Estimating and Projecting Trends in HIV/AIDS Generalized Epidemics Using Incremental Mixture Importance Sampling," Biometrics, The International Biometric Society, vol. 66(4), pages 1162-1173, December.
    • Handle: RePEc:bla:biomet:v:66:y:2010:i:4:p:1162-1173
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2010.01399.x
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    References listed on IDEAS

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    1. Liang, Faming & Liu, Chuanhai & Carroll, Raymond J., 2007. "Stochastic Approximation in Monte Carlo Computation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 305-320, March.
    2. Nicolas Chopin, 2002. "A sequential particle filter method for static models," Biometrika, Biometrika Trust, vol. 89(3), pages 539-552, August.
    3. Jasra, Ajay & Doucet, Arnaud & Stephens, David A. & Holmes, Christopher C., 2008. "Interacting sequential Monte Carlo samplers for trans-dimensional simulation," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 1765-1791, January.
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    Cited by:

    1. Sanchez-Romero, Miguel & Schuster, Philip & Prskawetz, Alexia, 2021. "Redistributive effects of pension reforms: Who are the winners and losers?," ECON WPS - Working Papers in Economic Theory and Policy 06/2021, TU Wien, Institute of Statistics and Mathematical Methods in Economics, Economics Research Unit.
    2. Brajendra K Singh & Moses J Bockarie & Manoj Gambhir & Peter M Siba & Daniel J Tisch & James Kazura & Edwin Michael, 2013. "Sequential Modelling of the Effects of Mass Drug Treatments on Anopheline-Mediated Lymphatic Filariasis Infection in Papua New Guinea," PLOS ONE, Public Library of Science, vol. 8(6), pages 1-16, June.
    3. repec:jss:jstsof:43:i02 is not listed on IDEAS
    4. Sánchez-Romero, Miguel & Schuster, Philip & Prskawetz, Alexia, 2024. "Redistributive effects of pension reforms: who are the winners and losers?," Journal of Pension Economics and Finance, Cambridge University Press, vol. 23(2), pages 294-320, April.
    5. Quentin Clairon & Chloé Pasin & Irene Balelli & Rodolphe Thiébaut & Mélanie Prague, 2024. "Parameter estimation in nonlinear mixed effect models based on ordinary differential equations: an optimal control approach," Computational Statistics, Springer, vol. 39(6), pages 2975-3005, September.
    6. Campbell, David & Lele, Subhash, 2014. "An ANOVA test for parameter estimability using data cloning with application to statistical inference for dynamic systems," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 257-267.
    7. Samuel J. Clark & Jason Thomas & Le Bao, 2012. "Estimates of Age-Specific Reductions in HIV Prevalence in Uganda: Bayesian Melding Estimation and Probabilistic Population Forecast with an HIV-enabled Cohort Component Projection Model," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 27(26), pages 743-774.
    8. Ševčíková, Hana & Raftery, Adrian E., 2016. "bayesPop: Probabilistic Population Projections," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 75(i05).
    9. David Sharrow & Samuel J. Clark & Mark Collinson & Kathleen Kahn & Stephen Tollman, 2013. "The age pattern of increases in mortality affected by HIV," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 29(39), pages 1039-1096.

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