forecast v3.07
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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 | |
BoxCox | Box Cox Transformation | |
Acf | (Partial) Autocorrelation Function Estimation | |
dshw | Double-Seasonal Holt-Winters Forecasting | |
dm.test | Diebold-Mariano test for predictive accuracy | |
croston | Forecasts for intermittent demand using Croston's method | |
arima.errors | ARIMA errors | |
ets | Exponential smoothing state space model | |
forecast.Arima | Forecasting using ARIMA or ARFIMA models | |
accuracy | Accuracy measures for forecast model | |
decompose | Classical Seasonal Decomposition by Moving Averages | |
rwf | Random Walk Forecast | |
auto.arima | Fit best ARIMA model to univariate time series | |
BoxCox.lambda | Automatic selection of Box Cox transformation parameter | |
arfima | Fit a fractionally differenced ARFIMA model | |
ses | Exponential smoothing forecasts | |
forecast.ets | Forecasting using ETS models | |
na.interp | Interpolate missing values in a time series | |
forecast.HoltWinters | Forecasting using Holt-Winters objects | |
ma | Moving-average smoothing | |
logLik.ets | Log-Likelihood of an ets object | |
forecast.stl | Forecasting using stl objects | |
CV | Cross-validation statistic | |
splinef | Cubic Spline Forecast | |
ndiffs | Number of differences required for a stationary series | |
seasadj | Seasonal adjustment | |
taylor | Half-hourly electricity demand | |
forecast | Forecasting time series | |
naive | Naive forecasts | |
forecast.lm | Forecast a linear model with possible time series components | |
forecast.StructTS | Forecasting using Structural Time Series models | |
tslm | Fit a linear model with time series components | |
seasonplot | Seasonal plot | |
seasonaldummy | Seasonal dummy variables | |
plot.ets | Plot components from ETS model | |
gold | Daily morning gold prices | |
monthdays | Number of days in each season | |
simulate.ets | Simulation from a time series model | |
gas | Australian monthly gas production | |
meanf | Mean Forecast | |
woolyrnq | Quarterly production of woollen yarn in Australia | |
tsdisplay | Time series display | |
thetaf | Theta method forecast | |
Arima | Fit ARIMA model to univariate time series | |
wineind | Australian total wine sales | |
subset.ts | Subsetting a time series | |
sindexf | Forecast seasonal index | |
plot.forecast | Forecast plot | |
fitted.Arima | One-step in-sample forecasts using ARIMA models | |
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Details
Date | 2011-10-11 |
LazyData | yes |
LazyLoad | yes |
License | GPL (>= 2) |
URL | http://robjhyndman.com/software/forecast/ |
Packaged | 2011-10-11 12:08:34 UTC; Rob |
Repository | CRAN |
Date/Publication | 2011-10-11 15:24:10 |
depends | base (>= 2.0.0) , fracdiff , graphics , R (>= 2.0.0) , stats , tseries , zoo |
Contributors | Rob Hyndman |
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