forecast v3.19
0
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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 | |
| monthdays | Number of days in each season | |
| Arima | Fit ARIMA model to univariate time series | |
| ndiffs | Number of differences required for a stationary series | |
| subset.ts | Subsetting a time series | |
| arfima | Fit a fractionally differenced ARFIMA model | |
| forecast.Arima | Forecasting using ARIMA or ARFIMA models | |
| rwf | Random Walk Forecast | |
| seasonaldummy | Seasonal dummy variables | |
| croston | Forecasts for intermittent demand using Croston's method | |
| accuracy | Accuracy measures for forecast model | |
| BoxCox | Box Cox Transformation | |
| tslm | Fit a linear model with time series components | |
| logLik.ets | Log-Likelihood of an ets object | |
| plot.ets | Plot components from ETS model | |
| seasadj | Seasonal adjustment | |
| thetaf | Theta method forecast | |
| naive | Naive forecasts | |
| arima.errors | ARIMA errors | |
| ma | Moving-average smoothing | |
| auto.arima | Fit best ARIMA model to univariate time series | |
| taylor | Half-hourly electricity demand | |
| CV | Cross-validation statistic | |
| forecast | Forecasting time series | |
| forecast.HoltWinters | Forecasting using Holt-Winters objects | |
| Acf | (Partial) Autocorrelation Function Estimation | |
| forecast.StructTS | Forecasting using Structural Time Series models | |
| tsdisplay | Time series display | |
| bats | BATS model (Exponential smoothing state space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components) | |
| forecast.bats | Forecasting using BATS and TBATS models | |
| splinef | Cubic Spline Forecast | |
| plot.forecast | Forecast plot | |
| simulate.ets | Simulation from a time series model | |
| na.interp | Interpolate missing values in a time series | |
| BoxCox.lambda | Automatic selection of Box Cox transformation parameter | |
| gas | Australian monthly gas production | |
| gold | Daily morning gold prices | |
| ets | Exponential smoothing state space model | |
| seasonplot | Seasonal plot | |
| forecast.stl | Forecasting using stl objects | |
| meanf | Mean Forecast | |
| msts | Multi-Seasonal Time Series | |
| forecast.lm | Forecast a linear model with possible time series components | |
| ses | Exponential smoothing forecasts | |
| fitted.Arima | One-step in-sample forecasts using ARIMA models | |
| sindexf | Forecast seasonal index | |
| woolyrnq | Quarterly production of woollen yarn in Australia | |
| dm.test | Diebold-Mariano test for predictive accuracy | |
| wineind | Australian total wine sales | |
| tbats | TBATS model (Exponential smoothing state space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components) | |
| forecast.ets | Forecasting using ETS models | |
| dshw | Double-Seasonal Holt-Winters Forecasting | |
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Details
| Date | 2012-02-22 |
| LinkingTo | Rcpp, RcppArmadillo |
| LazyData | yes |
| ByteCompile | TRUE |
| License | GPL (>= 2) |
| URL | http://robjhyndman.com/software/forecast/ |
| Packaged | 2012-02-22 05:45:20 UTC; hyndman |
| Repository | CRAN |
| Date/Publication | 2012-02-22 08:25:42 |
| depends | base (>= 2.14.0) , fracdiff , graphics , parallel , R (>= 2.14.0) , Rcpp (>= 0.9.10) , RcppArmadillo (>= 0.2.35) , stats , tseries , zoo |
| Contributors | Rob Hyndman |
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