forecast v3.07


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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
BoxCox Box Cox Transformation
Acf (Partial) Autocorrelation Function Estimation
dshw Double-Seasonal Holt-Winters Forecasting
dm.test Diebold-Mariano test for predictive accuracy
croston Forecasts for intermittent demand using Croston's method
arima.errors ARIMA errors
ets Exponential smoothing state space model
forecast.Arima Forecasting using ARIMA or ARFIMA models
accuracy Accuracy measures for forecast model
decompose Classical Seasonal Decomposition by Moving Averages
rwf Random Walk Forecast
auto.arima Fit best ARIMA model to univariate time series
BoxCox.lambda Automatic selection of Box Cox transformation parameter
arfima Fit a fractionally differenced ARFIMA model
ses Exponential smoothing forecasts
forecast.ets Forecasting using ETS models
na.interp Interpolate missing values in a time series
forecast.HoltWinters Forecasting using Holt-Winters objects
ma Moving-average smoothing
logLik.ets Log-Likelihood of an ets object
forecast.stl Forecasting using stl objects
CV Cross-validation statistic
splinef Cubic Spline Forecast
ndiffs Number of differences required for a stationary series
seasadj Seasonal adjustment
taylor Half-hourly electricity demand
forecast Forecasting time series
naive Naive forecasts
forecast.lm Forecast a linear model with possible time series components
forecast.StructTS Forecasting using Structural Time Series models
tslm Fit a linear model with time series components
seasonplot Seasonal plot
seasonaldummy Seasonal dummy variables
plot.ets Plot components from ETS model
gold Daily morning gold prices
monthdays Number of days in each season
simulate.ets Simulation from a time series model
gas Australian monthly gas production
meanf Mean Forecast
woolyrnq Quarterly production of woollen yarn in Australia
tsdisplay Time series display
thetaf Theta method forecast
Arima Fit ARIMA model to univariate time series
wineind Australian total wine sales
subset.ts Subsetting a time series
sindexf Forecast seasonal index
plot.forecast Forecast plot
fitted.Arima One-step in-sample forecasts using ARIMA models
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Last month downloads


Date 2011-10-11
LazyData yes
LazyLoad yes
License GPL (>= 2)
Packaged 2011-10-11 12:08:34 UTC; Rob
Repository CRAN
Date/Publication 2011-10-11 15:24:10

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