forecast v5.3


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by Rob Hyndman

Forecasting functions for time series and linear models

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
monthdays Number of days in each season
wineind Australian total wine sales
ses Exponential smoothing forecasts
BoxCox Box Cox Transformation
na.interp Interpolate missing values in a time series
Acf (Partial) Autocorrelation Function Estimation
gas Australian monthly gas production
tbats TBATS model (Exponential smoothing state space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components)
plot.bats Plot components from BATS model
arima.errors ARIMA errors
gold Daily morning gold prices
forecast.bats Forecasting using BATS and TBATS models
thetaf Theta method forecast
ndiffs Number of differences required for a stationary series
easter Easter holidays in each season
ets Exponential smoothing state space model
accuracy Accuracy measures for forecast model
fitted.Arima One-step in-sample forecasts using ARIMA models
forecast.stl Forecasting using stl objects
dshw Double-Seasonal Holt-Winters Forecasting
arfima Fit a fractionally differenced ARFIMA model
subset.ts Subsetting a time series
forecast.lm Forecast a linear model with possible time series components
ma Moving-average smoothing
taylor Half-hourly electricity demand
plot.ets Plot components from ETS model
woolyrnq Quarterly production of woollen yarn in Australia
Arima Fit ARIMA model to univariate time series
logLik.ets Log-Likelihood of an ets object
plot.forecast Forecast plot
naive Naive forecasts
seasonaldummy Seasonal dummy variables
tsclean Identify and replace outliers and missing values in a time series
tbats.components Extract components of a TBATS model
dm.test Diebold-Mariano test for predictive accuracy
forecast.Arima Forecasting using ARIMA or ARFIMA models
forecast Forecasting time series
tsdisplay Time series display
BoxCox.lambda Automatic selection of Box Cox transformation parameter
msts Multi-Seasonal Time Series
seasadj Seasonal adjustment
sindexf Forecast seasonal index
bizdays Number of trading days in each season
forecast.StructTS Forecasting using Structural Time Series models
nnetar Neural Network Time Series Forecasts
auto.arima Fit best ARIMA model to univariate time series
getResponse Get response variable from time series model.
tsoutliers Identify and replace outliers in a time series
arimaorder Return the order of an ARIMA or ARFIMA model
tslm Fit a linear model with time series components
forecast.HoltWinters Forecasting using Holt-Winters objects
bats BATS model (Exponential smoothing state space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components)
forecast.ets Forecasting using ETS models
simulate.ets Simulation from a time series model
CV Cross-validation statistic
croston Forecasts for intermittent demand using Croston's method
seasonplot Seasonal plot
splinef Cubic Spline Forecast
meanf Mean Forecast
rwf Random Walk Forecast
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LinkingTo Rcpp (>= 0.11.0), RcppArmadillo (>= 0.2.35)
LazyData yes
ByteCompile TRUE
License GPL (>= 2)
Packaged 2014-03-24 10:46:14 UTC; hyndman
NeedsCompilation yes
Repository CRAN
Date/Publication 2014-03-24 13:26:43

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