forecast v3.13

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

Date 2011-11-19
LazyData yes
License GPL (>= 2)
URL http://robjhyndman.com/software/forecast/
Packaged 2011-11-20 10:02:00 UTC; Rob
Repository CRAN
Date/Publication 2011-11-20 10:24:56

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