README.md
In robertsy/assimilr: Local Ensemble Kalman Particle Filters
assimilr
Two localized algorithms based on the EnKPF: the naive-LEnKPF and the block-LEnKPF.
Description
Implementation of two new local algorithms based on the EnKPF (Frei & Kunsch 2013):
the naive-LEnKPF and the block-LEnKPF. For details see Robert & Kunsch 2017.
The algorithms are tested on the modified SWEQ model of Wursch & Craig 2014,
here implemented in fortran90 for better performance.
Instructions
To install the package use devtools::install_github("robertsy/assimilr") or simply clone the repo and install the package locally. The folder example provides some basic usage of the main functions,
once for a one-step assimilation in a one-dimensional Gaussian random field and then for more complicated cases with the modified
SWEQ model.
robertsy/assimilr documentation built on May 27, 2019, 10:33 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
assimilr
Two localized algorithms based on the EnKPF: the naive-LEnKPF and the block-LEnKPF.
Description
Implementation of two new local algorithms based on the EnKPF (Frei & Kunsch 2013): the naive-LEnKPF and the block-LEnKPF. For details see Robert & Kunsch 2017.
The algorithms are tested on the modified SWEQ model of Wursch & Craig 2014, here implemented in fortran90 for better performance.
Instructions
To install the package use devtools::install_github("robertsy/assimilr") or simply clone the repo and install the package locally. The folder example provides some basic usage of the main functions, once for a one-step assimilation in a one-dimensional Gaussian random field and then for more complicated cases with the modified SWEQ model.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.