MCMC & sampling
48 methods in this family.
Featured
Bayesian DCC-GARCHBayesian DCC-GARCH estimates time-varying correlations across multiple financial or economic series by combining Engle's DCC-GARCH structure with Bayesian inference. Rather than maBayesian Gaussian Mixture ModelThe Bayesian Gaussian Mixture Model places prior distributions over all mixture parameters and infers their posteriors — typically via Variational Bayes or MCMC — rather than fittiBayesian Phylogenetic AnalysisBayesian phylogenetic analysis uses Bayes' theorem and Markov chain Monte Carlo (MCMC) sampling to estimate the posterior probability distribution over phylogenetic trees and modelBayesian Probit modelThe Bayesian Probit model is a binary regression method that models the probability of a binary outcome using the normal CDF (probit link) within a Bayesian framework. It assigns pDynamic Hamiltonian Monte CarloDynamic Hamiltonian Monte Carlo — widely known as the No-U-Turn Sampler (NUTS) — is an adaptive extension of Hamiltonian Monte Carlo that automatically selects the number of leapfrDynamic Metropolis-Hastings AlgorithmThe Dynamic Metropolis-Hastings (Dynamic MH) algorithm applies the Metropolis-Hastings MCMC sampler to Bayesian state-space and time-varying parameter models. At each time step, la
All methods 48
Bayesian DCC-GARCHBayesian Gaussian Mixture ModelBayesian Phylogenetic AnalysisBayesian Probit modelDynamic Hamiltonian Monte CarloDynamic Metropolis-Hastings AlgorithmDynamic Particle FilterDynamic Sequential Monte CarloGibbs SamplingGibbs Sampling for Model ComparisonGibbs Sampling with Measurement ErrorGibbs Sampling with Missing DataHamiltonian Monte CarloHamiltonian Monte Carlo with Measurement ErrorHamiltonian Monte Carlo with Missing DataHierarchical Hamiltonian Monte CarloHierarchical Markov Chain Monte CarloHierarchical Particle FilterMCMCMCMC for Model ComparisonMCMC with Measurement ErrorMCMC with missing dataMetropolis-Hastings AlgorithmMetropolis-Hastings for model comparisonMetropolis-Hastings with measurement errorMetropolis-Hastings with Missing DataMultilevel Gibbs SamplingMultilevel Hamiltonian Monte CarloMultilevel MCMCMultilevel Metropolis-HastingsNo-U-Turn SamplerParticle FilterParticle Filter with Measurement ErrorParticle Filter with Missing DataRobust Gibbs SamplingRobust Hamiltonian Monte CarloRobust Markov chain Monte CarloRobust Particle FilterRobust Sequential Monte CarloSequential Monte CarloSequential Monte Carlo with Measurement ErrorSequential Monte Carlo with Missing DataSlice SamplingSpatial Gibbs SamplingSpatial MCMCTime series MCMCTime series particle filterTime series sequential Monte Carlo