The forecast package is a comprehensive R package for time series analysis and forecasting. It provides functions for building, assessing, and using univariate forecasting models (e.g. ARIMA, exponential smoothing, etc.), tools for automatic model selection, diagnostics, plotting, forecasting future values, etc. It's widely used in statistics, economics, business forecasting, environmental science, etc. Exponential smoothing state space models (ETS) including seasonal components. Residual checks, model accuracy, plots, forecast error measures etc.
Features
- Automatic ARIMA model fitting with functions like auto.arima() to choose orders etc.
- Exponential smoothing state space models (ETS) including seasonal components etc.
- Forecasting functions to produce forecasts for future horizons, with prediction intervals etc.
- Diagnostic tools: residual checks, model accuracy, plots, forecast error measures etc.
- Support for other models/methods: neural network forecast, structural time series models, ARFIMA etc.
- Graphical plotting: autoplot(), ggplot2 integration, seasonal decomposition, etc.
Project Samples
Categories
Data VisualizationFollow forecast
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