forecastHybrid

Automated ensemble forecasting with ARIMA, ETS, STLM, TBATS, and neural networks.

EmergingOpen SourceLow lock-in

Pricing

Free tier

Flat rate

Adoption

Stable

License

Open Source

Data freshness

Unverified

Overview

What is forecastHybrid?

ForecastHybrid is an R package that automates the process of creating ensembles from various time series models including ARIMA, ETS, STL, TBATS, and neural networks. It simplifies cross-validation and model selection for more accurate forecasting.

Key differentiator

ForecastHybrid stands out by automating the ensemble process, making it easier for users to leverage multiple models without manual intervention.

Capability profile

Capability Radar

Ease of StartEcosystemValueMaturityFlexibilityScale Ready

Honest assessment

Strengths & Weaknesses

↑ Strengths

Automated ensemble forecastingmedium

Cross-validation of multiple modelsmedium

Support for ARIMA, ETS, STL, TBATS, and neural networksmedium

Simplified model selection processmedium

↓ Weaknesses

Limited to R users, not accessible for developers in other languageshigh

ForecastHybrid is an R package and does not have equivalents or bindings for other programming languages.

Performance issues with large datasetsmedium

Ensemble forecasting on large time series data can be computationally expensive, leading to slower processing times.

Documentation lacks depth and examples for advanced use caseshigh

The documentation primarily covers basic usage scenarios but falls short in explaining how to handle more complex forecasting tasks or customize the models further.

Fit analysis

Who is it for?

✓ Best for

R users who need to quickly generate accurate forecasts using multiple models

Researchers and analysts looking for a streamlined approach to time series analysis

✕ Not a fit for

Users requiring real-time forecasting capabilities

Projects that require integration with non-R environments

Cost structure

Pricing

Free Tier

Available

Open source — free to use

Starts at

$0

Model

Flat rate

Enterprise

None

Performance benchmarks

How Fast Is It?

Ecosystem

Relationships

Next step

Get Started with forecastHybrid

Step-by-step setup guide with code examples and common gotchas.

View Setup Guide →