forecast v4.04
0
Monthly downloads
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 | |
| fitted.Arima | One-step in-sample forecasts using ARIMA models | |
| meanf | Mean Forecast | |
| auto.arima | Fit best ARIMA model to univariate time series | |
| nnetar | Neural Network Time Series Forecasts | |
| sindexf | Forecast seasonal index | |
| forecast.bats | Forecasting using BATS and TBATS models | |
| msts | Multi-Seasonal Time Series | |
| ses | Exponential smoothing forecasts | |
| tsdisplay | Time series display | |
| ma | Moving-average smoothing | |
| forecast.lm | Forecast a linear model with possible time series components | |
| logLik.ets | Log-Likelihood of an ets object | |
| seasonplot | Seasonal plot | |
| forecast.stl | Forecasting using stl objects | |
| CV | Cross-validation statistic | |
| dshw | Double-Seasonal Holt-Winters Forecasting | |
| croston | Forecasts for intermittent demand using Croston's method | |
| forecast.StructTS | Forecasting using Structural Time Series models | |
| forecast.HoltWinters | Forecasting using Holt-Winters objects | |
| taylor | Half-hourly electricity demand | |
| ndiffs | Number of differences required for a stationary series | |
| simulate.ets | Simulation from a time series model | |
| forecast.ets | Forecasting using ETS models | |
| monthdays | Number of days in each season | |
| plot.forecast | Forecast plot | |
| tbats.components | Extract components of a TBATS model | |
| naive | Naive forecasts | |
| gas | Australian monthly gas production | |
| seasadj | Seasonal adjustment | |
| dm.test | Diebold-Mariano test for predictive accuracy | |
| na.interp | Interpolate missing values in a time series | |
| rwf | Random Walk Forecast | |
| splinef | Cubic Spline Forecast | |
| gold | Daily morning gold prices | |
| accuracy | Accuracy measures for forecast model | |
| plot.bats | Plot components from BATS model | |
| tbats | TBATS model (Exponential smoothing state space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components) | |
| wineind | Australian total wine sales | |
| forecast.Arima | Forecasting using ARIMA or ARFIMA models | |
| Arima | Fit ARIMA model to univariate time series | |
| plot.ets | Plot components from ETS model | |
| subset.ts | Subsetting a time series | |
| BoxCox | Box Cox Transformation | |
| ets | Exponential smoothing state space model | |
| tslm | Fit a linear model with time series components | |
| woolyrnq | Quarterly production of woollen yarn in Australia | |
| BoxCox.lambda | Automatic selection of Box Cox transformation parameter | |
| arfima | Fit a fractionally differenced ARFIMA model | |
| bats | BATS model (Exponential smoothing state space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components) | |
| getResponse | Get response variable from time series model. | |
| forecast | Forecasting time series | |
| Acf | (Partial) Autocorrelation Function Estimation | |
| arima.errors | ARIMA errors | |
| thetaf | Theta method forecast | |
| seasonaldummy | Seasonal dummy variables | |
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Details
| Date | 2013-04-22 |
| LinkingTo | Rcpp, RcppArmadillo |
| LazyData | yes |
| ByteCompile | TRUE |
| License | GPL (>= 2) |
| URL | http://robjhyndman.com/software/forecast/ |
| Packaged | 2013-04-22 10:53:42 UTC; hyndman |
| NeedsCompilation | yes |
| Repository | CRAN |
| Date/Publication | 2013-04-22 16:55:45 |
| depends | base (>= 2.14.0) , graphics , R (>= 2.14.0) , stats |
| imports | colorspace , fracdiff , nnet , parallel , Rcpp (>= 0.9.10) , RcppArmadillo (>= 0.2.35) , tseries , zoo |
| Contributors | Rob Hyndman |
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