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forecast (version 2.01)

Forecasting functions for time series

Description

Methods and tools for displaying and analysing univariate time series forecasts including exponential smoothing via state space models and automatic ARIMA modelling.

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Version

Install

install.packages('forecast')

Monthly Downloads

137,850

Version

2.01

License

GPL (>= 2)

Maintainer

Rob Hyndman

Last Published

September 18th, 2009

Functions in forecast (2.01)

Forecasting using ARIMA models

Forecasting using ETS models

Australian monthly gas production

Daily morning gold prices

forecast.HoltWinters

Forecasting using Holt-Winters objects

Forecasts for intermittent demand using Croston's method

Log-Likelihood of an ets object

One-step in-sample forecasts using ARIMA models

Accuracy measures for forecast model

Box Cox Transformation

Cubic Spline Forecast

Forecasting time series

Exponential smoothing state space model

Fit ARIMA model to univariate time series

Plot components from ETS model

Simulation from an ETS model

Time series display

Seasonal dummy variables

Forecast seasonal index

Number of days in each season

Exponential smoothing forecasts

Interpolate missing values in a time series

Random Walk Forecast

Seasonal adjustment

Quarterly production of woollen yarn in Australia

Australian total wine sales

forecast.StructTS

Forecasting using Structural Time Series models

Theta method forecast

Number of differences

Fit best ARIMA model to univariate time series

Diebold-Mariano test for predictive accuracy