forecast v3.08


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


Date 2011-10-15
LazyData yes
LazyLoad yes
License GPL (>= 2)
Packaged 2011-10-15 10:19:19 UTC; Rob
Repository CRAN
Date/Publication 2011-10-15 19:53:07

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