goestimate alternatives and similar packages
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gonum
Gonum is a set of numeric libraries for the Go programming language. It contains libraries for matrices, statistics, optimization, and more 
gosl
Linear algebra, eigenvalues, FFT, Bessel, elliptic, orthogonal polys, geometry, NURBS, numerical quadrature, 3D transfinite interpolation, random numbers, Mersenne twister, probability distributions, optimisation, differential equations. 
gonum/mat64
DISCONTINUED. The general purpose package for matrix computation. Package mat64 provides basic linear algebra operations for float64 matrices. 
TextRank
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sparse
Sparse matrix formats for linear algebra supporting scientific and machine learning applications 
triangolatte
2D triangulation library. Allows translating lines and polygons (both based on points) to the language of GPUs. 
PiHex
PiHex Library, written in Go, generates a hexadecimal number sequence in the number Pi in the range from 0 to 10,000,000. 
GoStats
GoStats is a go library for math statistics mostly used in ML domains, it covers most of the statistical measures functions. 
mudlarkgo
DISCONTINUED. A collection of packages providing (hopefully) useful code for use in software using Google's Go programming language.
InfluxDB  Power RealTime Data Analytics at Scale
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README
goestimate: State estimation and filtering algorithms in Go
This package offers a small suite of basic filtering algorithms written in Go. It currently provides the implementations of the following filters and estimators:
 Bootstrap Filter also known as SIR Particle filter
 Unscented Kalman Filter also known as Sigmapoint filter
 Extended Kalman Filter also known as Nonlinear Kalman Filter
 Kalman Filter also known as Linear Kalman Filter
In addition it provides an implementation of Rauchâ€“Tungâ€“Striebel smoothing for Kalman filter, which is an optimal Gaussian smoothing algorithm. There are variants for both LKF
(Linear Kalman Filter) and EKF
(Extended Kalman Filter) implemented in the smooth
package. UKF
smoothing will be implemented in the future.
Get started
Get the package:
$ go get github.com/milosgajdos/goestimate
Get dependencies:
$ make dep
Run unit tests:
$ make test
You can find various examples of usage in goestimateexamples.
TODO
 [ ] Square Root filter
 [ ] Information Filter
 [x] Smoothing
 Rauchâ€“Tungâ€“Striebel for both KF and EKF has been implemented in
smooth
package
 Rauchâ€“Tungâ€“Striebel for both KF and EKF has been implemented in
Contributing
YES PLEASE!
*Note that all licence references and agreements mentioned in the goestimate README section above
are relevant to that project's source code only.