forecast v3.10

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

Date 2011-10-27
LazyData yes
License GPL (>= 2)
URL http://robjhyndman.com/software/forecast/
Packaged 2011-10-27 04:00:20 UTC; hyndman
Repository CRAN
Date/Publication 2011-10-27 05:45:53

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