forecast v4.01

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

Date 2013-01-22
LinkingTo Rcpp, RcppArmadillo
LazyData yes
ByteCompile TRUE
License GPL (>= 2)
URL http://robjhyndman.com/software/forecast/
Packaged 2013-01-22 03:32:35 UTC; hyndman
Repository CRAN
Date/Publication 2013-01-22 08:23:33

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