https://github.com/fipelle/messytimeseriesoptim.jl
A Julia implementation of estimation and validation algorithms for time series compatible with incomplete data.
https://github.com/fipelle/messytimeseriesoptim.jl
dynamic-factor-models ecm-algorithm forecast julia kalman-filter kalman-smoother time-series var-models vma-models
Last synced: 8 months ago
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A Julia implementation of estimation and validation algorithms for time series compatible with incomplete data.
- Host: GitHub
- URL: https://github.com/fipelle/messytimeseriesoptim.jl
- Owner: fipelle
- License: bsd-3-clause
- Created: 2021-11-27T05:25:00.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2024-02-14T15:50:14.000Z (over 2 years ago)
- Last Synced: 2024-03-15T01:03:44.368Z (over 2 years ago)
- Topics: dynamic-factor-models, ecm-algorithm, forecast, julia, kalman-filter, kalman-smoother, time-series, var-models, vma-models
- Language: Julia
- Homepage:
- Size: 481 KB
- Stars: 6
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
A Julia implementation of estimation and validation algorithms for time series compatible with incomplete data.
| **Documentation** |
|:-------------------------------------------------------------------------------:
| [![][docs-stable-img]][docs-stable-url] [![][docs-dev-img]][docs-dev-url] |
## Installation
The package can be installed with the Julia package manager.
From the Julia REPL, type `]` to enter the Pkg REPL mode and run:
```
pkg> add MessyTimeSeriesOptim
```
Or, equivalently, via the `Pkg` API:
```julia
julia> import Pkg; Pkg.add("MessyTimeSeriesOptim")
```
[docs-dev-img]: https://img.shields.io/badge/docs-dev-blue.svg
[docs-dev-url]: https://fipelle.github.io/MessyTimeSeriesOptim.jl/dev
[docs-stable-img]: https://img.shields.io/badge/docs-stable-blue.svg
[docs-stable-url]: https://fipelle.github.io/MessyTimeSeriesOptim.jl/stable