forecast v4.7

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

Date 2013-09-26
LinkingTo Rcpp, RcppArmadillo
LazyData yes
ByteCompile TRUE
License GPL (>= 2)
URL http://robjhyndman.com/software/forecast/
Packaged 2013-09-27 00:02:02 UTC; hyndman
NeedsCompilation yes
Repository CRAN
Date/Publication 2013-09-27 07:54:57

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