LV_example_dataset      Data from a Lotka-Volterra ODE system with 2
                        species and 4 parameters. Species in order are:
                        1. Sheep (Prey) 2. Wolves (Predators)
agm                     Main function for adaptive gradient matching
doMCMC                  Main MCMC function Runs the MCMC for the
                        specified number of iterations and returns the
                        sampled parameter values
getODEGradient          Calculate gradients from ODE system
proposeParamsMCMC       Sample from proposal distribution for MCMC
sigmoidVarKernCompute   Compute K(x, x2) for sigmoid kernel, used by
                        gptk
sigmoidVarKernDiagCompute
                        Compute diagonal of sigmoid kernel (used by
                        gptk).
sigmoidVarKernExpandParam
                        Insert parameters into sigmoid kernel (used by
                        gptk)
sigmoidVarKernExtractParam
                        Auxiliary function for sigmoid kernel (used by
                        gptk)
sigmoidVarKernGradient
                        Compute gradient of sigmoid kernel with respect
                        to each parameter (used by gptk)
sigmoidVarKernParamInit
                        Auxiliary function for sigmoid kernel (used by
                        gptk)
solveODE                Solve ODE system explicitly.
