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forecast (version 2.02)

Forecasting functions for time series

Description

Methods and tools for displaying and analysing univariate time series forecasts including exponential smoothing via state space models and automatic ARIMA modelling.

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Version

Install

install.packages('forecast')

Monthly Downloads

142,544

Version

2.02

License

GPL (>= 2)

Maintainer

Rob Hyndman

Last Published

December 23rd, 2009

Functions in forecast (2.02)

seasonaldummy

Seasonal dummy variables
ses

Exponential smoothing forecasts
arima.errors

ARIMA errors
meanf

Mean Forecast
forecast.ets

Forecasting using ETS models
ets

Exponential smoothing state space model
thetaf

Theta method forecast
BoxCox

Box Cox Transformation
sindexf

Forecast seasonal index
croston

Forecasts for intermittent demand using Croston's method
seasonplot

Seasonal plot
forecast.Arima

Forecasting using ARIMA models
splinef

Cubic Spline Forecast
logLik.ets

Log-Likelihood of an ets object
Arima

Fit ARIMA model to univariate time series
forecast

Forecasting time series
monthdays

Number of days in each season
ndiffs

Number of differences
forecast.HoltWinters

Forecasting using Holt-Winters objects
accuracy

Accuracy measures for forecast model
wineind

Australian total wine sales
dm.test

Diebold-Mariano test for predictive accuracy
seasadj

Seasonal adjustment
gold

Daily morning gold prices
plot.forecast

Forecast plot
fitted.Arima

One-step in-sample forecasts using ARIMA models
plot.ets

Plot components from ETS model
na.interp

Interpolate missing values in a time series
gas

Australian monthly gas production
tsdisplay

Time series display
rwf

Random Walk Forecast
auto.arima

Fit best ARIMA model to univariate time series
forecast.StructTS

Forecasting using Structural Time Series models
simulate.ets

Simulation from an ETS model
woolyrnq

Quarterly production of woollen yarn in Australia