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The kernel ridge regression and the gradient matching algorithm proposed in Niu et al. (2016) <https://proceedings.mlr.press/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.
| Version: | 1.0.4 |
| Depends: | R (≥ 3.2.0) |
| Imports: | R6, pracma, pspline, mvtnorm, graphics |
| Published: | 2022-08-19 |
| Author: | Mu Niu [aut, cre] |
| Maintainer: | Mu Niu <mu.niu at glasgow.ac.uk> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | KGode results |
| Reference manual: | KGode.pdf |
| Package source: | KGode_1.0.4.tar.gz |
| Windows binaries: | r-devel: KGode_1.0.4.zip, r-release: KGode_1.0.4.zip, r-oldrel: KGode_1.0.4.zip |
| macOS binaries: | r-release (arm64): KGode_1.0.4.tgz, r-oldrel (arm64): KGode_1.0.4.tgz, r-release (x86_64): KGode_1.0.4.tgz, r-oldrel (x86_64): KGode_1.0.4.tgz |
| Old sources: | KGode archive |
| Reverse imports: | shinyKGode |
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