forecast v5.7

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by Rob Hyndman

Forecasting functions for time series and linear models

Methods and tools for displaying and analysing univariate time series forecasts including exponential smoothing via state space models and automatic ARIMA modelling.

Functions in forecast

Name Description
Arima Fit ARIMA model to univariate time series
auto.arima Fit best ARIMA model to univariate time series
plot.ets Plot components from ETS model
accuracy Accuracy measures for forecast model
CV Cross-validation statistic
fitted.Arima One-step in-sample forecasts using ARIMA models
dshw Double-Seasonal Holt-Winters Forecasting
forecast.HoltWinters Forecasting using Holt-Winters objects
ets Exponential smoothing state space model
BoxCox.lambda Automatic selection of Box Cox transformation parameter
gold Daily morning gold prices
forecast.StructTS Forecasting using Structural Time Series models
tbats.components Extract components of a TBATS model
splinef Cubic Spline Forecast
monthdays Number of days in each season
tslm Fit a linear model with time series components
tsclean Identify and replace outliers and missing values in a time series
seasonaldummy Seasonal dummy variables
arfima Fit a fractionally differenced ARFIMA model
woolyrnq Quarterly production of woollen yarn in Australia
forecast.lm Forecast a linear model with possible time series components
tsoutliers Identify and replace outliers in a time series
seasadj Seasonal adjustment
bats BATS model (Exponential smoothing state space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components)
simulate.ets Simulation from a time series model
forecast.ets Forecasting using ETS models
BoxCox Box Cox Transformation
wineind Australian total wine sales
rwf Random Walk Forecast
easter Easter holidays in each season
seasonplot Seasonal plot
forecast.bats Forecasting using BATS and TBATS models
na.interp Interpolate missing values in a time series
plot.bats Plot components from BATS model
taylor Half-hourly electricity demand
getResponse Get response variable from time series model.
dm.test Diebold-Mariano test for predictive accuracy
arimaorder Return the order of an ARIMA or ARFIMA model
plot.forecast Forecast plot
gas Australian monthly gas production
croston Forecasts for intermittent demand using Croston's method
nnetar Neural Network Time Series Forecasts
sindexf Forecast seasonal index
logLik.ets Log-Likelihood of an ets object
ses Exponential smoothing forecasts
findfrequency Find dominant frequency of a time series
thetaf Theta method forecast
naive Naive forecasts
msts Multi-Seasonal Time Series
arima.errors ARIMA errors
ma Moving-average smoothing
forecast Forecasting time series
forecast.stl Forecasting using stl objects
meanf Mean Forecast
bizdays Number of trading days in each season
Acf (Partial) Autocorrelation Function Estimation
ndiffs Number of differences required for a stationary series
forecast.Arima Forecasting using ARIMA or ARFIMA models
tbats TBATS model (Exponential smoothing state space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components)
tsdisplay Time series display
subset.ts Subsetting a time series
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Details

Date 2014-12-17
LinkingTo Rcpp (>= 0.11.0), RcppArmadillo (>= 0.2.35)
LazyData yes
ByteCompile TRUE
BugReports https://github.com/robjhyndman/forecast/issues
License GPL (>= 2)
URL http://github.com/robjhyndman/forecast
Packaged 2014-12-17 05:16:03 UTC; hyndman
NeedsCompilation yes
Repository CRAN
Date/Publication 2014-12-17 07:21:28

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