Component-wise markov chain monte carlo: Uniform and geometric ergodicity under mixing and composition

Mathematics

• Uniform Ergodicity 100%
• Geometric Ergodicity 89%
• Markov Chain Monte Carlo 65%
• Update 62%
• Metropolis-Hastings 34%
• Strategy 26%
• Markov chain 20%
• Simulation 16%
• Linear Mixed Model 16%
• Gibbs Sampler 15%
• Random Sequence 14%
• Mixed Model 14%
• Conditional Distribution 13%
• Stationary Distribution 12%
• Maximum Likelihood Estimation 11%
• Identically distributed 11%
• Convergence Properties 11%
• Target 10%
• Rate of Convergence 9%
• Converge 8%
• Performance 7%

Business & Economics

• Ergodicity 93%
• Markov Chain Monte Carlo 76%
• Mixed Model 53%
• Markov Chain 46%
• Maximum Likelihood Estimation 39%
• Gibbs Sampler 32%
• Simulation 28%
• Stationary Distribution 27%
• Conditional Distribution 25%
• Limited Attention 24%
• Performance 8%