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

DOI10.1111/j.1541-0420.2010.01399.xzbMath1233.62185OpenAlexW1987443112WikidataQ28749602 ScholiaQ28749602MaRDI QIDQ3076046

Le Bao, Adrian E. Raftery

Publication date: 17 February 2011

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc2925068

zbMATH Keywords

prevalenceMarkov chain Monte CarloBayesian model selectionBayesian model averagingepidemiological modelintegrated likelihoodsampling importance resamplingBayesian meldingsusceptible infected removed model

Mathematics Subject Classification ID

Related Items (14)

An ANOVA test for parameter estimability using data cloning with application to statistical inference for dynamic systems ⋮ Fast Bayesian inversion for high dimensional inverse problems ⋮ Implicit estimation of ecological model parameters ⋮ A regularization method for the parameter estimation problem in ordinary differential equations via discrete optimal control theory ⋮ Estimating HIV epidemics for subnational areas ⋮ Langevin incremental mixture importance sampling ⋮ Comments on: Inference for size demography from point pattern data using integral projection models ⋮ Microsimulation Model Calibration using Incremental Mixture Approximate Bayesian Computation ⋮ Estimating and Projecting Trends in HIV/AIDS Generalized Epidemics Using Incremental Mixture Importance Sampling ⋮ Adaptive Incremental Mixture Markov Chain Monte Carlo ⋮ Incremental Mixture Importance Sampling With Shotgun Optimization ⋮ Modeling of the HIV infection epidemic in the Netherlands: a multi-parameter evidence synthesis approach ⋮ Integrating geostatistical maps and infectious disease transmission models using adaptive multiple importance sampling ⋮ Adaptive Multiple Importance Sampling

Uses Software

• CODA
• WinBUGS
• LBFGS-B
• Mcmcpack
• UNAIDS
• mcmc

Cites Work

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• Probabilistic projections of HIV prevalence using Bayesian melding
• Optimal scaling for partially updating MCMC algorithms
• Interacting sequential Monte Carlo samplers for trans-dimensional simulation
• Bayesian model averaging: A tutorial. (with comments and a rejoinder).
• Inference from iterative simulation using multiple sequences
• Model uncertainty
• Following a Moving Target—Monte Carlo Inference for Dynamic Bayesian Models
• Estimating and Projecting Trends in HIV/AIDS Generalized Epidemics Using Incremental Mixture Importance Sampling
• Local Adaptive Importance Sampling for Multivariate Densities With Strong Nonlinear Relationships
• Adaptive mixture importance sampling
• Sequential Imputations and Bayesian Missing Data Problems
• Model Selection and Accounting for Model Uncertainty in Graphical Models Using Occam's Window
• Nonparametric Importance Sampling
• A sequential particle filter method for static models
• Dynamically Weighted Importance Sampling in Monte Carlo Computation
• Safe and Effective Importance Sampling
• Inference for Deterministic Simulation Models: The Bayesian Melding Approach
• Weighted Average Importance Sampling and Defensive Mixture Distributions
• Inference from a Deterministic Population Dynamics Model for Bowhead Whales
• Bayes Factors
• A Limited Memory Algorithm for Bound Constrained Optimization
• Integration of Multimodal Functions by Monte Carlo Importance Sampling
• Stochastic Approximation in Monte Carlo Computation
• A dynamic modelling strategy for Bayesian computer model emulation

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