Entry point for running a Beast task, for instance an MCMC or other probabilistic analysis, a simulation, etc.
MCMC chain. This is the main element that controls which posterior to calculate, how long to run the chain and all other properties, which operators to apply on the state space and where to log results.
Runs multiple MCMC chains in parallel and reports Rubin-Gelman statistic while running the chain for each item in the first log file as well as the maximum difference in clade probability for every pair of chains. Note that log file names should have $(seed) in their name so that the first chain uses the actual seed in the file name and all subsequent chains add one to it.Furthermore, the log and tree log should have the same sample frequency.
Bouckaert, Remco, Timothy G. Vaughan, Joëlle Barido-Sottani, Sebastián Duchêne, Mathieu Fourment, Alexandra Gavryushkina, Joseph Heled, Graham Jones, Denise Kühnert, Nicola De Maio, Michael Matschiner, Fábio K. Mendes, Nicola F. Müller, Huw A. Ogilvie, Louis du Plessis, Alex Popinga, Andrew Rambaut, David Rasmussen, Igor Siveroni, Marc A. Suchard, Chieh-Hsi Wu, Dong Xie, Chi Zhang, Tanja Stadler, Alexei J. Drummond BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis. PLoS computational biology 15, no. 4 (2019): e1006650.
doi:10.1371/journal.pcbi.1006650
chains, chainLength, state, init, storeEvery, preBurnin, numInitializationAttempts, distribution, operator, logger, sampleFromPrior, operatorschedule
| type: java.lang.Integer |
| number of chains to run in parallel (default 2) |
| Optional input. Default: 2 |
| type: java.lang.Long |
| Length of the MCMC chain i.e. number of samples taken in main loop |
| Required input |
| type: beast.base.inference.State |
| elements of the state space |
| Optional input |
| type: beast.base.inference.StateNodeInitialiser*** |
| one or more state node initilisers used for determining the start state of the chain |
| Optional input |
| type: java.lang.Integer |
| store the state to disk every X number of samples so that we can resume computation later on if the process failed half-way. |
| Optional input. Default: -1 |
| type: java.lang.Integer |
| Number of burn in samples taken before entering the main loop |
| Optional input. Default: 0 |
| type: java.lang.Integer |
| Number of initialization attempts before failing (default=10) |
| Optional input. Default: 10 |
| type: beast.base.inference.Distribution |
| probability distribution to sample over (e.g. a posterior) |
| Required input |
| type: beast.base.inference.Operator*** |
| operator for generating proposals in MCMC state space |
| Optional input |
| type: beast.base.inference.Logger*** |
| loggers for reporting progress of MCMC chain |
| Required input |
| type: java.lang.Boolean |
| whether to ignore the likelihood when sampling (default false). The distribution with id 'likelihood' in the posterior input will be ignored when this flag is set. |
| Optional input. Default: false |
| type: beast.base.inference.OperatorSchedule |
| specify operator selection and optimisation schedule |
| Required input |