estimator: State-space estimation algorithms such as Kalman Filters
The goal of this library is to simplify implementation and use of state-space estimation algorithms, such as Kalman Filters. The interface for constructing models is isolated as much as possible from the specifics of a given algorithm, so swapping out a Kalman Filter for a Bayesian Particle Filter should involve a minimum of effort.
This implementation is designed to support symbolic types, such as from sbv or ivory. As a result you can generate code in another language, such as C, from a model written using this package; or run static analyses on your model.
Also included is a sophisticated sensor fusion example in Numeric.Estimator.Model.SensorFusion, which may be useful in its own right.
Make warnings errors
Use -f <flag> to enable a flag, or -f -<flag> to disable that flag. More info
- estimator-220.127.116.11.tar.gz [browse] (Cabal source package)
- Package description (as included in the package)
For package maintainers and hackage trustees
|Versions [RSS]||1.0.0, 18.104.22.168, 22.214.171.124, 126.96.36.199, 188.8.131.52|
|Dependencies||ad (>=4.2), base (>=4.6 && <5), distributive (>=0.4), lens (>=4.6), linear (>=1.15), reflection (>=1.5) [details]|
|Copyright||2014 Galois, Inc.|
|Category||Math, Numerical, Statistics|
|Source repo||this: git clone https://github.com/GaloisInc/estimator(tag 184.108.40.206)|
|Uploaded||by JameySharp at 2014-12-10T23:55:31Z|
|Reverse Dependencies||1 direct, 0 indirect [details]|
|Downloads||3780 total (1 in the last 30 days)|
|Rating||(no votes yet) [estimated by Bayesian average]|
|Status||Docs uploaded by user
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