forecast v2.01


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by Rob Hyndman

Forecasting functions for time series

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

Functions in forecast

Name Description
forecast.Arima Forecasting using ARIMA models
forecast.ets Forecasting using ETS models
gas Australian monthly gas production
gold Daily morning gold prices
forecast.HoltWinters Forecasting using Holt-Winters objects
plot.forecast Forecast plot
croston Forecasts for intermittent demand using Croston's method
logLik.ets Log-Likelihood of an ets object
fitted.Arima One-step in-sample forecasts using ARIMA models
accuracy Accuracy measures for forecast model
BoxCox Box Cox Transformation
splinef Cubic Spline Forecast
forecast Forecasting time series
ets Exponential smoothing state space model
Arima Fit ARIMA model to univariate time series
plot.ets Plot components from ETS model
seasonplot Seasonal plot
simulate.ets Simulation from an ETS model
tsdisplay Time series display
seasonaldummy Seasonal dummy variables
sindexf Forecast seasonal index
monthdays Number of days in each season
ses Exponential smoothing forecasts
na.interp Interpolate missing values in a time series
rwf Random Walk Forecast
seasadj Seasonal adjustment
woolyrnq Quarterly production of woollen yarn in Australia
wineind Australian total wine sales
forecast.StructTS Forecasting using Structural Time Series models
meanf Mean Forecast
thetaf Theta method forecast
ndiffs Number of differences
auto.arima Fit best ARIMA model to univariate time series
dm.test Diebold-Mariano test for predictive accuracy
arima.errors ARIMA errors
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Last month downloads


Date 2009-09-14
LazyData yes
LazyLoad yes
License GPL (>= 2)
Packaged 2009-09-14 07:27:37 UTC; hyndman
Repository CRAN
Date/Publication 2009-09-18 20:24:40

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