Package

Forecast package

forecast-package

Forecasting Functions for Time Series and Linear Models

Time series analysis

Functions for working with time series

msts()

Multi-Seasonal Time Series

subset(<ts>) subset(<msts>)

Subsetting a time series

bizdays()

Number of trading days in each season

easter()

Easter holidays in each season

monthdays()

Number of days in each season

fourier() fourierf()

Fourier terms for modelling seasonality

seasonaldummy() seasonaldummyf()

Seasonal dummy variables

findfrequency()

Find dominant frequency of a time series

BoxCox() InvBoxCox()

Box Cox Transformation

BoxCox.lambda()

Automatic selection of Box Cox transformation parameter

tsclean()

Identify and replace outliers and missing values in a time series

tsoutliers()

Identify and replace outliers in a time series

na.interp()

Interpolate missing values in a time series

ndiffs()

Number of differences required for a stationary series

nsdiffs()

Number of differences required for a seasonally stationary series

bld.mbb.bootstrap()

Box-Cox and Loess-based decomposition bootstrap.

is.constant()

Is an object constant?

Seasonal decomposition

Functions used in seasonal decomposition

ma()

Moving-average smoothing

mstl()

Multiple seasonal decomposition

seasadj()

Seasonal adjustment

seasonal() trendcycle() remainder()

Extract components from a time series decomposition

Modelling

Functions for estimating time series models

arfima()

Fit a fractionally differenced ARFIMA model

Arima()

Fit ARIMA model to univariate time series

auto.arima()

Fit best ARIMA model to univariate time series

ets()

Exponential smoothing state space model

baggedModel() baggedETS()

Forecasting using a bagged model

bats()

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

tbats()

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

nnetar()

Neural Network Time Series Forecasts

forecast(<stl>) stlm() forecast(<stlm>) stlf()

Forecasting using stl objects

tslm()

Fit a linear model with time series components

Forecasting

Functions for producing forecasts

rwf() naive() snaive()

Naive and Random Walk Forecasts

meanf()

Mean Forecast

ses() holt() hw()

Exponential smoothing forecasts

dshw()

Double-Seasonal Holt-Winters Forecasting

forecast(<stl>) stlm() forecast(<stlm>) stlf()

Forecasting using stl objects

splinef()

Cubic Spline Forecast

thetaf()

Theta method forecast

croston()

Forecasts for intermittent demand using Croston's method

sindexf()

Forecast seasonal index

forecast()

Forecasting time series

forecast(<fracdiff>) forecast(<Arima>) forecast(<ar>)

Forecasting using ARIMA or ARFIMA models

forecast(<ets>)

Forecasting using ETS models

forecast(<baggedModel>)

Forecasting using a bagged model

forecast(<bats>) forecast(<tbats>)

Forecasting using BATS and TBATS models

forecast(<HoltWinters>)

Forecasting using Holt-Winters objects

forecast(<lm>)

Forecast a linear model with possible time series components

forecast(<mlm>)

Forecast a multiple linear model with possible time series components

forecast(<mts>)

Forecasting time series

forecast(<nnetar>)

Forecasting using neural network models

forecast(<StructTS>)

Forecasting using Structural Time Series models

Plotting

Functions for plotting time series and forecasts

gghistogram()

Histogram with optional normal and kernel density functions

ggseasonplot() seasonplot()

Seasonal plot

ggmonthplot() ggsubseriesplot()

Create a seasonal subseries ggplot

gglagplot() gglagchull()

Time series lag ggplots

Acf() Pacf() Ccf() taperedacf() taperedpacf()

(Partial) Autocorrelation and Cross-Correlation Function Estimation

autoplot(<acf>) ggAcf() ggPacf() ggCcf() autoplot(<mpacf>) ggtaperedacf() ggtaperedpacf()

ggplot (Partial) Autocorrelation and Cross-Correlation Function Estimation and Plotting

ggtsdisplay() tsdisplay()

Time series display

checkresiduals()

Check that residuals from a time series model look like white noise

plot(<Arima>) plot(<ar>) autoplot(<Arima>) autoplot(<ar>)

Plot characteristic roots from ARIMA model

plot(<bats>) autoplot(<tbats>) autoplot(<bats>) plot(<tbats>)

Plot components from BATS model

plot(<ets>) autoplot(<ets>)

Plot components from ETS model

plot(<forecast>) autoplot(<forecast>) autoplot(<splineforecast>) autolayer(<forecast>) plot(<splineforecast>)

Forecast plot

autoplot(<mforecast>) autolayer(<mforecast>) plot(<mforecast>)

Multivariate forecast plot

autoplot(<decomposed.ts>) autoplot(<stl>) autoplot(<StructTS>) autoplot(<seas>) autoplot(<mstl>)

Plot time series decomposition components using ggplot

autolayer(<mts>) autolayer(<msts>) autolayer(<ts>) autoplot(<ts>) autoplot(<mts>) autoplot(<msts>) fortify(<ts>)

Automatically create a ggplot for time series objects

autolayer()

Create a ggplot layer appropriate to a particular data type

Model analysis

Functions for analysing time series models

fitted(<fracdiff>) fitted(<Arima>) fitted(<ar>) fitted(<bats>) fitted(<ets>) fitted(<modelAR>) fitted(<nnetar>) fitted(<tbats>)

h-step in-sample forecasts for time series models.

residuals(<forecast>) residuals(<ar>) residuals(<Arima>) residuals(<bats>) residuals(<tbats>) residuals(<ets>) residuals(<fracdiff>) residuals(<nnetar>) residuals(<stlm>) residuals(<tslm>)

Residuals for various time series models

checkresiduals()

Check that residuals from a time series model look like white noise

arimaorder()

Return the order of an ARIMA or ARFIMA model

simulate(<ets>) simulate(<Arima>) simulate(<ar>) simulate(<fracdiff>) simulate(<nnetar>) simulate(<modelAR>)

Simulation from a time series model

tbats.components()

Extract components of a TBATS model

Forecast evaluation

Functions used for evaluating forecasts

accuracy()

Accuracy measures for a forecast model

CVar()

k-fold Cross-Validation applied to an autoregressive model

CV()

Cross-validation statistic

tsCV()

Time series cross-validation

dm.test()

Diebold-Mariano test for predictive accuracy

Data

Data sets included in the package

gas

Australian monthly gas production

gold

Daily morning gold prices

taylor

Half-hourly electricity demand

wineind

Australian total wine sales

woolyrnq

Quarterly production of woollen yarn in Australia