Crates.io | timers-rs |
lib.rs | timers-rs |
version | 0.1.3 |
source | src |
created_at | 2025-02-04 09:35:24.888774+00 |
updated_at | 2025-02-06 16:48:16.318559+00 |
description | Time series library for analysts, ML engineers, and data scientists. This package was actually built as a course module. |
homepage | |
repository | https://github.com/ravinthiranpartheepan1407/timers |
max_upload_size | |
id | 1541736 |
size | 23,013 |
This package was actually built as a course module. In the course, I cover the math behind each time series model and build everything from scratch without using any external crates. Check out this course here: https://www.udemy.com/course/build-an-open-source-time-series-lib-from-scratch-in-rust/?referralCode=802A036F5A6D7453BCBD
Library Modules:
arima arma autocorrelation autoregressive sarima seasonality ses sma stationarity trend whitenoise wma
Sample Usage:
use timers_rs::autocorrelation::autocorrelation;
use timers_rs::ses;
fn main() {
let series = vec![10.0, 12.0, 14.0, 16.0, 18.0, 20.0];
let model = ses::ExponentialSmoothing{
alpha: 0.5,
beta: Some(0.0),
};
let single_exponential_smoothing = model.single_exponential_smoothing(&series);
println!("Single Exponential Smoothing: {:?}", single_exponential_smoothing);
let autocorrelation_result = autocorrelation(&series, 2);
println!("Autocorrealtion Result {}", autocorrelation_result);
}