fitodeMCMC: Fit ordinary differential equations model using MCMC

Description

This function fits ordinary differential equations models to a uni- or multi-variate time series by MCMC using the Metropolis-Hastings update rule. It searches through the parameter space on link scales, which can provide more efficient posterior sampling.

Usage

fitodeMCMC(
  model,
  data,
  start,
  tcol = "times",
  proposal.vcov,
  prior = list(),
  chains = 1,
  iter = 2000,
  burnin = iter/2,
  thin = 1,
  refresh = max(iter/10, 1),
  prior.only = FALSE,
  link,
  fixed = list(),
  solver.opts = list(method = "rk4"),
  solver = ode,
  ...
)

Value

An object of class ``fitodeMCMC'' as described in fitodeMCMC-class.

Arguments

model: ode model
data: data frame with time column and observation column
start: named vector of starting parameter values
tcol: time column
proposal.vcov: variance-covariance matrix of a multivariate normal proposal distribution
prior: list of formulas specifying prior distributions
chains: (numeric) number of chains
iter: (numeric) number of iterations per chain
burnin: (numeric) number of burnin interations
thin: (numeric) thining interval between consecutive observations
refresh: (numeric) refresh interval
prior.only: (logical) sample from prior distribution only?
link: named vector or list of link functions for model parameters
fixed: named vector or list of model parameters to fix and their values
solver.opts: options for ode integration. See ode
solver: ode solver
...: additional arguments (unused)