stochastic-rs
| Crates.io | stochastic-rs |
| lib.rs | stochastic-rs |
| version | |
| source | src |
| created_at | 2023-05-28 09:05:46.785089+00 |
| updated_at | 2025-03-14 17:40:14.024631+00 |
| description | A Rust library for quant finance and simulating stochastic processes. |
| homepage | https://github.com/dancixx/stochastic-rs |
| repository | https://github.com/dancixx/stochastic-rs |
| max_upload_size | |
| id | 876339 |
| Cargo.toml error: | TOML parse error at line 17, column 1 | 17 | autolib = false | ^^^^^^^ unknown field `autolib`, expected one of `name`, `version`, `edition`, `authors`, `description`, `readme`, `license`, `repository`, `homepage`, `documentation`, `build`, `resolver`, `links`, `default-run`, `default_dash_run`, `rust-version`, `rust_dash_version`, `rust_version`, `license-file`, `license_dash_file`, `license_file`, `licenseFile`, `license_capital_file`, `forced-target`, `forced_dash_target`, `autobins`, `autotests`, `autoexamples`, `autobenches`, `publish`, `metadata`, `keywords`, `categories`, `exclude`, `include` |
| size | 0 |
Daniel Boros (dancixx)
documentation
README
stochastic-rs
stochastic-rs is a high-performance Rust library for simulating and analyzing stochastic processes. Designed for applications in quantitative finance, AI training, and statistical modeling, it provides efficient tools to generate synthetic data and analyze complex stochastic systems.
Installation
Add stochastic-rs to your Cargo.toml:
[dependencies]
stochastic-rs = "0.x.0"
Ensure you have Rust installed. Visit rust-lang.org for setup instructions.
Contributing
Contributions are welcome! Whether it's bug reports, feature suggestions, or documentation improvements, your help is appreciated. Open an issue or start a discussion on GitHub.
License
Licensed under the MIT License. See the LICENSE file for details.
Contact
For discussions, issues, or suggestions, feel free to open a GitHub issue or reach out at [dancixx@gmail.com].
Note: This library is in active development and may introduce breaking changes as it evolves. Feedback is encouraged!