forecast v3.21

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

Date 2012-04-26
LinkingTo Rcpp, RcppArmadillo
LazyData yes
ByteCompile TRUE
License GPL (>= 2)
URL http://robjhyndman.com/software/forecast/
Packaged 2012-04-30 02:31:26 UTC; hyndman
Repository CRAN
Date/Publication 2012-04-30 05:37:32

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