fitodeMCMC: Fit ordinary differential equations model using MCMC

In parksw3/fitode: Tools for Ordinary Differential Equations Model Fitting

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,
  ...
)

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)

Value

An object of class “fitodeMCMC” as described in fitodeMCMC-class.

See Also

fitodeMCMC

parksw3/fitode documentation built on April 3, 2024, 7:45 a.m.