VMCMC

VMCMC processes Markov Chain Monte Carlo (MCMC) traces to perform automatic burn-in estimation and convergence assessment for Bayesian inference and phylogenetic parameter estimation.

Key Features:

• MCMC trace post-processing: Processes MCMC traces for post-analysis of Bayesian inference results.
• Automatic burn-in estimation: Provides automatic estimation of burn-in periods from MCMC traces.
• Convergence assessment: Performs comprehensive convergence diagnostics on MCMC traces.
• Parameter exploration: Enables exploration of continuous and tree parameters derived from MCMC output.
• Posterior distribution analysis: Facilitates assessment of posterior distributions and parameter value estimation from MCMC samples.

Scientific Applications:

• Bayesian phylogenetic inference: Post-processes MCMC output from Bayesian phylogenetic analyses to assess convergence and burn-in.
• Parameter estimation: Assists estimation and interpretation of posterior distributions and parameter values from MCMC.
• Large-scale MCMC studies: Supports convergence assessment and burn-in determination in large-scale MCMC studies.

Methodology:

Post-processes MCMC traces to estimate burn-in, assess convergence, and support exploration of continuous and tree parameters.