forecast v3.14

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

Date 2011-12-09
LinkingTo Rcpp, RcppArmadillo
LazyData yes
ByteCompile TRUE
License GPL (>= 2)
URL http://robjhyndman.com/software/forecast/
Packaged 2011-12-09 04:06:17 UTC; hyndman
Repository CRAN
Date/Publication 2011-12-09 09:16:24

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