doMCMC: Main MCMC function Runs the MCMC for the specified number of...
In deGradInfer: Parameter Inference for Systems of Differential Equation

Main MCMC function Runs the MCMC for the specified number of iterations and returns the sampled parameter values

1	doMCMC(timePoints, data, auxVars, options)

`timePoints`	Measured time points for the ODE system.
`data`	Observed data.
`auxVars`	Auxiliary variables.
`options`	Options for MCMC run.

Function returns a list with elements parameters, the sampled ODE parameters for the current MCMC iteration, tuning, the inferred tuning parameters for acceptance of the MCMC moves, paramsRec, the sampled ODE parameters recorded over all MCMC iterations, lLRec, the log likelihood recorded over all MCMC iterations, xRec, the samples from the Gaussian process of the latent variables recorded over all MCMC iterations, gpRec, the samples of the hyperparameters for the Gaussian process recorded over all MCMC iterations, timePoints, the time points, noiseRec, the standard deviation of the observational noise recorded over all MCMC iterations (currently fixed), swappedChains, the number of times the chains have been swapped, chainNums, the number of chains, maxIterations, the total number of MCMC iterations and lLAllChains, the log likelihood for all chains recorded over all MCMC iterations. If the user specifies temperMismatchParameter=FALSE, the function additionally returns gradientMismatchParameterRec, the sampled gradient mismatch parameters recorded over all MCMC iterations.