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forecast (version 2.06)

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

142,544

Version

2.06

License

GPL (>= 2)

Maintainer

Rob Hyndman

Last Published

July 29th, 2010

Functions in forecast (2.06)

Australian monthly gas production

Fit ARIMA model to univariate time series

forecast.HoltWinters

Forecasting using Holt-Winters objects

Number of differences

Random Walk Forecast

Fit a fractionally differenced ARFIMA model

Seasonal dummy variables

Plot components from ETS model

One-step in-sample forecasts using ARIMA models

Simulation from a time series model

Fit best ARIMA model to univariate time series

Interpolate missing values in a time series

Cubic Spline Forecast

Log-Likelihood of an ets object

Exponential smoothing state space model

Quarterly production of woollen yarn in Australia

Seasonal adjustment

Number of days in each season

Box Cox Transformation

forecast.StructTS

Forecasting using Structural Time Series models

Exponential smoothing forecasts

Theta method forecast

Daily morning gold prices

Forecast seasonal index

Forecasting time series

Diebold-Mariano test for predictive accuracy

Forecasts for intermittent demand using Croston's method

Forecasting using ARIMA or ARFIMA models

Time series display

Accuracy measures for forecast model

Forecasting using ETS models

Australian total wine sales