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forecast (version 4.03)

Forecasting functions for time series and linear models

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

4.03

License

GPL (>= 2)

Maintainer

Rob Hyndman

Last Published

March 17th, 2013

Functions in forecast (4.03)

forecast.Arima

Forecasting using ARIMA or ARFIMA models
sindexf

Forecast seasonal index
thetaf

Theta method forecast
tslm

Fit a linear model with time series components
wineind

Australian total wine sales
dshw

Double-Seasonal Holt-Winters Forecasting
ndiffs

Number of differences required for a stationary series
Arima

Fit ARIMA model to univariate time series
ses

Exponential smoothing forecasts
plot.forecast

Forecast plot
tbats

TBATS model (Exponential smoothing state space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components)
BoxCox

Box Cox Transformation
Acf

(Partial) Autocorrelation Function Estimation
na.interp

Interpolate missing values in a time series
simulate.ets

Simulation from a time series model
monthdays

Number of days in each season
seasonplot

Seasonal plot
CV

Cross-validation statistic
croston

Forecasts for intermittent demand using Croston's method
arima.errors

ARIMA errors
forecast.stl

Forecasting using stl objects
fitted.Arima

One-step in-sample forecasts using ARIMA models
seasadj

Seasonal adjustment
forecast.HoltWinters

Forecasting using Holt-Winters objects
seasonaldummy

Seasonal dummy variables
tsdisplay

Time series display
tbats.components

Extract components of a TBATS model
auto.arima

Fit best ARIMA model to univariate time series
accuracy

Accuracy measures for forecast model
splinef

Cubic Spline Forecast
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)
dm.test

Diebold-Mariano test for predictive accuracy
taylor

Half-hourly electricity demand
arfima

Fit a fractionally differenced ARFIMA model
forecast

Forecasting time series
logLik.ets

Log-Likelihood of an ets object
ma

Moving-average smoothing
meanf

Mean Forecast
woolyrnq

Quarterly production of woollen yarn in Australia
forecast.lm

Forecast a linear model with possible time series components
msts

Multi-Seasonal Time Series
forecast.bats

Forecasting using BATS and TBATS models
forecast.StructTS

Forecasting using Structural Time Series models
naive

Naive forecasts
plot.ets

Plot components from ETS model
forecast.ets

Forecasting using ETS models
getResponse

Get response variable from time series model.
plot.bats

Plot components from BATS model
nnetar

Neural Network Time Series Forecasts
subset.ts

Subsetting a time series
rwf

Random Walk Forecast
gas

Australian monthly gas production
gold

Daily morning gold prices
ets

Exponential smoothing state space model