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KGode

Kernel Based Gradient Matching for Parameter Inference in Ordinary Differential Equations

The kernel ridge regression and the gradient matching algorithm proposed in Niu et al. (2016) <http://jmlr.org/proceedings/papers/v48/niu16.html> and the warping algorithm proposed in Niu et al. (2017) <DOI:10.1007/s00180-017-0753-z> are implemented for parameter inference in differential equations. Four schemes are provided for improving parameter estimation in odes by using the odes regularisation and warping.

Functions (14)

Kernel

The 'Kernel' class object

MLP

The 'MLP' class object

RBF

The 'RBF' class object

Warp

The 'Warp' class object

bootstrap

The 'bootstrap' function

crossv

The 'crossv' function

diagnostic

The 'diagnostic' function

ode

The 'ode' class object

rkg

The 'rkg' function

rkg3

The 'rkg3' class object

rkhs

The 'rkhs' class object

third

The 'third' function

warpInitLen

The 'warpInitLen' function

warpfun

The 'warpfun' function

KGode

Kernel Based Gradient Matching for Parameter Inference in Ordinary Differential Equations

v1.0.3
GPL (>= 2)
Authors
Mu Niu [aut, cre]
Initial release

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