forecast v2.02

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

Date 2009-12-23
LazyData yes
LazyLoad yes
License GPL (>= 2)
URL http://www.robjhyndman.com/software/forecast/
Packaged 2009-12-23 06:59:19 UTC; hyndman
Repository CRAN
Date/Publication 2009-12-23 08:18:26

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