forecast v3.12
0
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by Rob Hyndman
Forecasting functions for time series
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 | |
| forecast.ets | Forecasting using ETS models | |
| plot.ets | Plot components from ETS model | |
| accuracy | Accuracy measures for forecast model | |
| CV | Cross-validation statistic | |
| gold | Daily morning gold prices | |
| BoxCox.lambda | Automatic selection of Box Cox transformation parameter | |
| ets | Exponential smoothing state space model | |
| croston | Forecasts for intermittent demand using Croston's method | |
| meanf | Mean Forecast | |
| forecast.HoltWinters | Forecasting using Holt-Winters objects | |
| BoxCox | Box Cox Transformation | |
| Arima | Fit ARIMA model to univariate time series | |
| Acf | (Partial) Autocorrelation Function Estimation | |
| auto.arima | Fit best ARIMA model to univariate time series | |
| plot.forecast | Forecast plot | |
| forecast.Arima | Forecasting using ARIMA or ARFIMA models | |
| arfima | Fit a fractionally differenced ARFIMA model | |
| simulate.ets | Simulation from a time series model | |
| logLik.ets | Log-Likelihood of an ets object | |
| dshw | Double-Seasonal Holt-Winters Forecasting | |
| dm.test | Diebold-Mariano test for predictive accuracy | |
| ma | Moving-average smoothing | |
| forecast | Forecasting time series | |
| forecast.StructTS | Forecasting using Structural Time Series models | |
| fitted.Arima | One-step in-sample forecasts using ARIMA models | |
| forecast.stl | Forecasting using stl objects | |
| seasonaldummy | Seasonal dummy variables | |
| na.interp | Interpolate missing values in a time series | |
| naive | Naive forecasts | |
| taylor | Half-hourly electricity demand | |
| subset.ts | Subsetting a time series | |
| splinef | Cubic Spline Forecast | |
| arima.errors | ARIMA errors | |
| rwf | Random Walk Forecast | |
| sindexf | Forecast seasonal index | |
| ses | Exponential smoothing forecasts | |
| seasonplot | Seasonal plot | |
| wineind | Australian total wine sales | |
| tslm | Fit a linear model with time series components | |
| tsdisplay | Time series display | |
| woolyrnq | Quarterly production of woollen yarn in Australia | |
| seasadj | Seasonal adjustment | |
| decompose | Classical Seasonal Decomposition by Moving Averages | |
| monthdays | Number of days in each season | |
| thetaf | Theta method forecast | |
| ndiffs | Number of differences required for a stationary series | |
| gas | Australian monthly gas production | |
| forecast.lm | Forecast a linear model with possible time series components | |
| No Results! | ||
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Details
| Date | 2011-11-16 |
| LazyData | yes |
| License | GPL (>= 2) |
| URL | http://robjhyndman.com/software/forecast/ |
| Packaged | 2011-11-16 02:17:25 UTC; hyndman |
| Repository | CRAN |
| Date/Publication | 2011-11-16 12:16:43 |
| depends | base (>= 2.0.0) , fracdiff , graphics , R (>= 2.0.0) , stats , tseries , zoo |
| Contributors | Rob Hyndman |
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