forecast v4.05

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

Date 2013-06-19
LinkingTo Rcpp, RcppArmadillo
LazyData yes
ByteCompile TRUE
License GPL (>= 2)
URL http://robjhyndman.com/software/forecast/
Packaged 2013-06-19 04:21:12 UTC; hyndman
NeedsCompilation yes
Repository CRAN
Date/Publication 2013-06-19 08:53:21

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