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) 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.
- Version1.0.4
- R version≥ 3.2.0
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- Last release08/19/2022
Documentation
Team
Mu Niu
Insights
Last 30 days
This package has been downloaded 174 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 2 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 2,582 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Jan 21, 2025 with 39 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports4 packages
- Reverse Imports1 package