de_mcmc {deBInfer} R Documentation

de_mcmc

Description

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

Usage

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,
...
)


Arguments

 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 cnt 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

Value

a debinfer_result object containing input parameters, data and MCMC samples

[Package deBInfer version 0.4.4 Index]