Reference

Basic modelling Functions for constructing models, via the fitmodel object.
fitmodel()	Constructor of fitmodel object
dTrajObs()	Log-likelihood of a trajectory for a deterministic model
rTrajObs()	Generate an observation trajectory for a fitmodel
dLogPosterior()	Posterior distribution for a fitmodel
testFitmodel()	Test a fitmodel
Stochastic modelling Methods for generating stochastic simulations
simulateModelStochastic()	Simulate forward a stochastic model
simulateModelReplicates()	Simulate several replicate of the model
Data Epidemiological datasets.
fluTdc1971	Time-series of the 1971 influenza epidemic in Tristan-da-Cunha
MCMC Functions related to Markov-chain Monte Carlo.
mcmcMh()	Metropolis-Hastings MCMC
burnAndThin()	Burn and thin MCMC chain
computeDic()	Compute the DIC
Particle filtering Functions for particle filtering.
particleFilter()	Run a particle filter for fitmodel object
margLogLikeSto()	Marginal log-likelihood for a stochastic model
ABC Functions for Approximate Bayesian Computation.
computeDistanceAbc()	Compute the distance between a model and data for ABC
distanceOscillation()	Distance weighted by number of oscillations
Plotting Functions for plotting model trajectories and fits.
plotEssBurn()	Plot Effective Sample Size (ESS) against burn-in
plotFit()	Plot fit of model to data
plotHPDregion2D()	2D highest posterior density region
plotPosteriorDensity()	Plot MCMC posterior densities
plotPosteriorFit()	Plot MCMC posterior fit
plotSMC()	Plot result of SMC
plotTrace()	Plot MCMC trace
plotTraj()	Plot model trajectories