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 |
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) |
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. |