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

forecast (version 3.07)

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

142,544

Version

3.07

License

GPL (>= 2)

Maintainer

Rob Hyndman

Last Published

October 11th, 2011

Functions in forecast (3.07)

BoxCox

Box Cox Transformation
Acf

(Partial) Autocorrelation Function Estimation
dshw

Double-Seasonal Holt-Winters Forecasting
dm.test

Diebold-Mariano test for predictive accuracy
croston

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

ARIMA errors
ets

Exponential smoothing state space model
forecast.Arima

Forecasting using ARIMA or ARFIMA models
accuracy

Accuracy measures for forecast model
decompose

Classical Seasonal Decomposition by Moving Averages
rwf

Random Walk Forecast
auto.arima

Fit best ARIMA model to univariate time series
BoxCox.lambda

Automatic selection of Box Cox transformation parameter
arfima

Fit a fractionally differenced ARFIMA model
ses

Exponential smoothing forecasts
forecast.ets

Forecasting using ETS models
na.interp

Interpolate missing values in a time series
forecast.HoltWinters

Forecasting using Holt-Winters objects
ma

Moving-average smoothing
logLik.ets

Log-Likelihood of an ets object
forecast.stl

Forecasting using stl objects
CV

Cross-validation statistic
splinef

Cubic Spline Forecast
ndiffs

Number of differences required for a stationary series
seasadj

Seasonal adjustment
taylor

Half-hourly electricity demand
forecast

Forecasting time series
naive

Naive forecasts
forecast.lm

Forecast a linear model with possible time series components
forecast.StructTS

Forecasting using Structural Time Series models
tslm

Fit a linear model with time series components
seasonplot

Seasonal plot
seasonaldummy

Seasonal dummy variables
plot.ets

Plot components from ETS model
gold

Daily morning gold prices
monthdays

Number of days in each season
simulate.ets

Simulation from a time series model
gas

Australian monthly gas production
meanf

Mean Forecast
woolyrnq

Quarterly production of woollen yarn in Australia
tsdisplay

Time series display
thetaf

Theta method forecast
Arima

Fit ARIMA model to univariate time series
wineind

Australian total wine sales
subset.ts

Subsetting a time series
sindexf

Forecast seasonal index
plot.forecast

Forecast plot
fitted.Arima

One-step in-sample forecasts using ARIMA models