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forecast (version 3.08)

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

3.08

License

GPL (>= 2)

Maintainer

Rob Hyndman

Last Published

October 15th, 2011

Functions in forecast (3.08)

auto.arima

Fit best ARIMA model to univariate time series
ses

Exponential smoothing forecasts
naive

Naive forecasts
ets

Exponential smoothing state space model
sindexf

Forecast seasonal index
forecast.HoltWinters

Forecasting using Holt-Winters objects
wineind

Australian total wine sales
ma

Moving-average smoothing
accuracy

Accuracy measures for forecast model
simulate.ets

Simulation from a time series model
BoxCox

Box Cox Transformation
gold

Daily morning gold prices
dm.test

Diebold-Mariano test for predictive accuracy
na.interp

Interpolate missing values in a time series
forecast.Arima

Forecasting using ARIMA or ARFIMA models
forecast.StructTS

Forecasting using Structural Time Series models
plot.forecast

Forecast plot
splinef

Cubic Spline Forecast
decompose

Classical Seasonal Decomposition by Moving Averages
ndiffs

Number of differences required for a stationary series
meanf

Mean Forecast
arima.errors

ARIMA errors
subset.ts

Subsetting a time series
arfima

Fit a fractionally differenced ARFIMA model
rwf

Random Walk Forecast
plot.ets

Plot components from ETS model
tsdisplay

Time series display
seasonplot

Seasonal plot
tslm

Fit a linear model with time series components
seasadj

Seasonal adjustment
woolyrnq

Quarterly production of woollen yarn in Australia
CV

Cross-validation statistic
forecast.stl

Forecasting using stl objects
forecast.ets

Forecasting using ETS models
thetaf

Theta method forecast
logLik.ets

Log-Likelihood of an ets object
BoxCox.lambda

Automatic selection of Box Cox transformation parameter
taylor

Half-hourly electricity demand
Acf

(Partial) Autocorrelation Function Estimation
seasonaldummy

Seasonal dummy variables
forecast.lm

Forecast a linear model with possible time series components
monthdays

Number of days in each season
forecast

Forecasting time series
fitted.Arima

One-step in-sample forecasts using ARIMA models
croston

Forecasts for intermittent demand using Croston's method
Arima

Fit ARIMA model to univariate time series
dshw

Double-Seasonal Holt-Winters Forecasting
gas

Australian monthly gas production