Learn R Programming
⚠️There's a newer version (8.24.0) of this package.Take me there.

forecast (version 3.14)

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.

Copy Link

Version

Install

install.packages('forecast')

Monthly Downloads

191,858

Version

3.14

License

GPL (>= 2)

Maintainer

Rob Hyndman

Last Published

December 9th, 2011

Functions in forecast (3.14)

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