forecast v2.13

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

Date 2011-02-16
LazyData yes
LazyLoad yes
License GPL (>= 2)
URL http://robjhyndman.com/software/forecast/
Packaged 2011-02-15 23:31:28 UTC; hyndman
Repository CRAN
Date/Publication 2011-02-16 11:36:46

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