Parameter Inference for Systems of Differential Equation


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Documentation for package ‘deGradInfer’ version 1.0.1

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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.