![]() 8 Sequential Monte Carlo, Particle MCMC, Iterated Filtering, and MCEM.7.13 Comparing different MCMCs with MCMCsuite and compareMCMCs.7.11.3 Customized log-likelihood evaluations: RW_llFunction sampler.7.10 Variable selection using Reversible Jump MCMC.7.6.3 Assessing the adaption process of RW and RW_block samplers.7.6.2 Measuring sampler computation times: getTimes.7.6.1 Rerunning versus restarting an MCMC.7.5 User-friendly execution of MCMC algorithms: runMCMC.7.2.2 Customizing the MCMC configuration.7.1 One-line invocation of MCMC: nimbleMCMC.6.2.2 Determining the nodes and variables in a model.6.2 NIMBLE models are objects you can query and manipulate.6.1.3 Making multiple instances from the same model definition. ![]()
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