de_mcmc {deBInfer} | R Documentation |

Bayesian inference for a deterministic DE model (with models solved via an DE solver) with an observation model.

```
de_mcmc(
N,
data,
de.model,
obs.model,
all.params,
ref.params = NULL,
ref.inits = NULL,
Tmax,
data.times,
cnt = 10,
plot = TRUE,
sizestep = 0.01,
solver = "ode",
verbose.mcmc = TRUE,
verbose = FALSE,
...
)
```

`N` |
integer, number of MCMC iterations |

`data` |
data.frame of time course observations to fit the model to. The observations must be ordered ascending by time. |

`de.model` |
a function defining a DE model, compliant with the solvers in deSolve or PBSddesolve |

`obs.model` |
a function defining an observation model. Must be a function with arguments 'data', 'sim.data', 'samp'. |

`all.params` |
debinfer_parlist containing all model, MCMC, and observation |

`ref.params` |
an optional named vector containing a set of reference parameters, e.g. the true parameters underlying a simulated data set |

`ref.inits` |
an optional named vector containing a set of reference initial values, e.g. the true initial values underlying a simulated data set |

`Tmax` |
maximum timestep for solver |

`data.times` |
time points for which observations are available |

`cnt` |
integer interval at which to print and possibly plot information on the current state of the MCMC chain |

`plot` |
logical, plot traces for all parameters at the interval defined by |

`sizestep` |
timestep for solver to return values at, only used if data.times is missing |

`solver` |
the solver to use. 1 or "ode" = deSolve::ode; 2 or "dde" = PBSddesolve::dde; 3 or "dede" = deSolve::dde |

`verbose.mcmc` |
logical display MCMC progress messages |

`verbose` |
logical display verbose solver output |

`...` |
further arguments to the solver |

a debinfer_result object containing input parameters, data and MCMC samples

[Package *deBInfer* version 0.4.4 Index]