forecast v3.10
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.lm | Forecast a linear model with possible time series components | |
| arima.errors | ARIMA errors | |
| forecast.Arima | Forecasting using ARIMA or ARFIMA models | |
| croston | Forecasts for intermittent demand using Croston's method | |
| Acf | (Partial) Autocorrelation Function Estimation | |
| forecast.HoltWinters | Forecasting using Holt-Winters objects | |
| splinef | Cubic Spline Forecast | |
| rwf | Random Walk Forecast | |
| ses | Exponential smoothing forecasts | |
| auto.arima | Fit best ARIMA model to univariate time series | |
| ma | Moving-average smoothing | |
| Arima | Fit ARIMA model to univariate time series | |
| plot.forecast | Forecast plot | |
| logLik.ets | Log-Likelihood of an ets object | |
| na.interp | Interpolate missing values in a time series | |
| gas | Australian monthly gas production | |
| decompose | Classical Seasonal Decomposition by Moving Averages | |
| BoxCox.lambda | Automatic selection of Box Cox transformation parameter | |
| gold | Daily morning gold prices | |
| accuracy | Accuracy measures for forecast model | |
| forecast.ets | Forecasting using ETS models | |
| monthdays | Number of days in each season | |
| seasadj | Seasonal adjustment | |
| sindexf | Forecast seasonal index | |
| forecast.stl | Forecasting using stl objects | |
| BoxCox | Box Cox Transformation | |
| forecast | Forecasting time series | |
| subset.ts | Subsetting a time series | |
| tslm | Fit a linear model with time series components | |
| arfima | Fit a fractionally differenced ARFIMA model | |
| forecast.StructTS | Forecasting using Structural Time Series models | |
| thetaf | Theta method forecast | |
| simulate.ets | Simulation from a time series model | |
| fitted.Arima | One-step in-sample forecasts using ARIMA models | |
| wineind | Australian total wine sales | |
| meanf | Mean Forecast | |
| plot.ets | Plot components from ETS model | |
| woolyrnq | Quarterly production of woollen yarn in Australia | |
| CV | Cross-validation statistic | |
| ets | Exponential smoothing state space model | |
| taylor | Half-hourly electricity demand | |
| tsdisplay | Time series display | |
| seasonaldummy | Seasonal dummy variables | |
| seasonplot | Seasonal plot | |
| ndiffs | Number of differences required for a stationary series | |
| naive | Naive forecasts | |
| dshw | Double-Seasonal Holt-Winters Forecasting | |
| dm.test | Diebold-Mariano test for predictive accuracy | |
| No Results! | ||
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Details
| Date | 2011-10-27 |
| LazyData | yes |
| License | GPL (>= 2) |
| URL | http://robjhyndman.com/software/forecast/ |
| Packaged | 2011-10-27 04:00:20 UTC; hyndman |
| Repository | CRAN |
| Date/Publication | 2011-10-27 05:45:53 |
| depends | base (>= 2.0.0) , fracdiff , graphics , R (>= 2.0.0) , stats , tseries , zoo |
| Contributors | Rob Hyndman |
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