Crate oxidiviner 

OxiDiviner

A comprehensive Rust library for time series analysis and forecasting.

Overview

OxiDiviner is a comprehensive library for time series analysis and forecasting, designed to provide efficient, accurate, and easy-to-use statistical models for Rust. This library includes all functionality in a single crate for ease of use.

Enhanced API Modules

OxiDiviner provides several enhanced API modules for different use cases:

• financial - Specialized functionality for financial time series analysis
• api - High-level unified interface for all forecasting models
• quick - One-line utility functions for rapid prototyping
• batch - Batch processing for multiple time series simultaneously

Quick Start

use oxidiviner::prelude::*;
use oxidiviner::quick;
use chrono::{Duration, Utc};

// Generate sample data
let start = Utc::now();
let timestamps: Vec<_> = (0..30).map(|i| start + Duration::days(i)).collect();
let values: Vec<f64> = (0..30).map(|i| 100.0 + i as f64 + (i as f64 * 0.1).sin() * 5.0).collect();

// Quick forecasting
let (forecast, model_used) = quick::auto_forecast(timestamps, values, 5)?;
println!("Used {} model, forecast: {:?}", model_used, forecast);

Re-exports

pub use api::ForecastBuilder;

pub use api::ForecastConfig;

pub use api::ForecastOutput;

pub use api::Forecaster;

pub use api::ModelParameters;

pub use api::ModelType;

pub use batch::BatchConfig;

pub use batch::BatchForecastResult;

pub use batch::BatchModelType;

pub use batch::BatchTimeSeries;

pub use financial::FinancialTimeSeries;

pub use financial::ModelComparison;

pub use financial::ModelResult;

pub use adaptive::AdaptiveBuilder;

pub use adaptive::AdaptiveConfig;

pub use adaptive::MarketRegime;

pub use adaptive::RealTimeQualitySystem;

pub use adaptive::RegimeDetector;

pub use models::autoregressive::ARIMAModel;

pub use models::autoregressive::ARMAModel;

pub use models::autoregressive::ARModel;

pub use models::autoregressive::SARIMAModel;

pub use models::autoregressive::VARModel;

pub use models::exponential_smoothing::DailyETSModel;

pub use models::exponential_smoothing::DampedTrendModel;

pub use models::exponential_smoothing::ETSComponent;

pub use models::exponential_smoothing::ETSModel;

pub use models::exponential_smoothing::HoltLinearModel;

pub use models::exponential_smoothing::HoltWintersModel;

pub use models::exponential_smoothing::MinuteETSModel;

pub use models::exponential_smoothing::SimpleESModel;

pub use models::garch::EGARCHModel;

pub use models::garch::GARCHMModel;

pub use models::garch::GARCHModel;

pub use models::garch::GJRGARCHModel;

pub use models::garch::RiskPremiumType;

pub use models::moving_average::MAModel;

pub use models::cointegration::VECMModel;

pub use models::decomposition::STLModel;

pub use models::nonlinear::TARModel;

pub use models::regime_switching::MarkovSwitchingModel;

pub use models::state_space::KalmanFilter;

pub use crate::core::*;

Modules

adaptive

Adaptive Forecasting System

advanced

Advanced API for specialized use cases

api

High-level API module

batch

Batch processing module

builder

Builder API namespace for fluent model construction

convenience

Convenience functions for quick forecasting

core

OxiDiviner Core

ensemble

Ensemble Forecasting Methods

financial

Financial time series analysis module

math

models

OxiDiviner Models

optimization

Parameter Optimization Engine

prelude

Prelude module for convenient imports

quick

Quick utilities module