A B C D E F G H I L M N P R S T W
accuracy | Accuracy measures for forecast model |
Acf | (Partial) Autocorrelation and Cross-Correlation Function Estimation |
arfima | Fit a fractionally differenced ARFIMA model |
Arima | Fit ARIMA model to univariate time series |
arima.errors | ARIMA errors |
arimaorder | Return the order of an ARIMA or ARFIMA model |
auto.arima | Fit best ARIMA model to univariate time series |
autoplot.acf | ggplot (Partial) Autocorrelation and Cross-Correlation Function Estimation |
autoplot.Arima | Plot characteristic roots from ARIMA model |
autoplot.decomposed.ts | ggplot of a decomposed time series object |
autoplot.ets | Plot components from ETS model |
autoplot.forecast | Forecast plot |
autoplot.mforecast | Multivariate forecast plot |
autoplot.mpacf | ggplot (Partial) Autocorrelation and Cross-Correlation Function Estimation |
autoplot.mts | Automatically create a ggplot for time series objects |
autoplot.splineforecast | Forecast plot |
autoplot.stl | ggplot STL object |
autoplot.ts | Automatically create a ggplot for time series objects |
bats | BATS model (Exponential smoothing state space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components) |
best.arima | Fit best ARIMA model to univariate time series |
bizdays | Number of trading days in each season |
BoxCox | Box Cox Transformation |
BoxCox.lambda | Automatic selection of Box Cox transformation parameter |
Ccf | (Partial) Autocorrelation and Cross-Correlation Function Estimation |
croston | Forecasts for intermittent demand using Croston's method |
CV | Cross-validation statistic |
dm.test | Diebold-Mariano test for predictive accuracy |
dshw | Double-Seasonal Holt-Winters Forecasting |
easter | Easter holidays in each season |
ets | Exponential smoothing state space model |
findfrequency | Find dominant frequency of a time series |
fitted.Arima | One-step in-sample forecasts using ARIMA models |
forecast | Forecasting time series |
forecast.ar | Forecasting using ARIMA or ARFIMA models |
forecast.Arima | Forecasting using ARIMA or ARFIMA models |
forecast.bats | Forecasting using BATS and TBATS models |
forecast.default | Forecasting time series |
forecast.ets | Forecasting using ETS models |
forecast.fracdiff | Forecasting using ARIMA or ARFIMA models |
forecast.HoltWinters | Forecasting using Holt-Winters objects |
forecast.lm | Forecast a linear model with possible time series components |
forecast.mlm | Forecast a multiple linear model with possible time series components |
forecast.mts | Forecasting time series |
forecast.nnetar | Neural Network Time Series Forecasts |
forecast.stl | Forecasting using stl objects |
forecast.stlm | Forecasting using stl objects |
forecast.StructTS | Forecasting using Structural Time Series models |
forecast.tbats | Forecasting using BATS and TBATS models |
forecast.ts | Forecasting time series |
fortify.forecast | Fortify a forecast object to data.frame for ggplot |
fortify.ts | Automatically create a ggplot for time series objects |
fourier | Seasonal dummy variables |
fourierf | Seasonal dummy variables |
gas | Australian monthly gas production |
GeomForecast | Forecast plot |
geom_forecast | Forecast plot |
getResponse | Get response variable from time series model. |
ggAcf | ggplot (Partial) Autocorrelation and Cross-Correlation Function Estimation |
ggCcf | ggplot (Partial) Autocorrelation and Cross-Correlation Function Estimation |
ggmonthplot | Create a seasonal subseries ggplot |
ggPacf | ggplot (Partial) Autocorrelation and Cross-Correlation Function Estimation |
ggseasonplot | Seasonal plot |
ggtaperedacf | ggplot (Partial) Autocorrelation and Cross-Correlation Function Estimation |
ggtaperedpacf | ggplot (Partial) Autocorrelation and Cross-Correlation Function Estimation |
ggtsdisplay | Time series display |
gold | Daily morning gold prices |
holt | Exponential smoothing forecasts |
hw | Exponential smoothing forecasts |
InvBoxCox | Box Cox Transformation |
is.acf | Is an object a particular model type? |
is.Arima | Is an object a particular model type? |
is.bats | Is an object a particular model type? |
is.constant | Is an object constant? |
is.ets | Is an object a particular model type? |
is.forecast | Is an object a particular forecast type? |
is.mforecast | Is an object a particular forecast type? |
is.nnetar | Is an object a particular model type? |
is.nnetarmodels | Is an object a particular model type? |
is.splineforecast | Is an object a particular forecast type? |
is.stlm | Is an object a particular model type? |
logLik.ets | Log-Likelihood of an ets object |
ma | Moving-average smoothing |
meanf | Mean Forecast |
mforecast | Forecasting time series |
monthdays | Number of days in each season |
msts | Multi-Seasonal Time Series |
na.interp | Interpolate missing values in a time series |
naive | Naive forecasts |
ndiffs | Number of differences required for a stationary series |
nnetar | Neural Network Time Series Forecasts |
nsdiffs | Number of differences required for a stationary series |
Pacf | (Partial) Autocorrelation and Cross-Correlation Function Estimation |
plot.ar | Plot characteristic roots from ARIMA model |
plot.Arima | Plot characteristic roots from ARIMA model |
plot.bats | Plot components from BATS model |
plot.ets | Plot components from ETS model |
plot.forecast | Forecast plot |
plot.mforecast | Multivariate forecast plot |
plot.splineforecast | Forecast plot |
plot.tbats | Plot components from BATS model |
print.forecast | Forecasting time series |
print.mforecast | Forecasting time series |
rwf | Random Walk Forecast |
seasadj | Seasonal adjustment |
seasonaldummy | Seasonal dummy variables |
seasonaldummyf | Seasonal dummy variables |
seasonplot | Seasonal plot |
ses | Exponential smoothing forecasts |
simulate.ar | Simulation from a time series model |
simulate.Arima | Simulation from a time series model |
simulate.ets | Simulation from a time series model |
simulate.fracdiff | Simulation from a time series model |
sindexf | Forecast seasonal index |
snaive | Naive forecasts |
splinef | Cubic Spline Forecast |
StatForecast | Forecast plot |
stl | Forecasting using stl objects |
stlf | Forecasting using stl objects |
stlm | Forecasting using stl objects |
subset.ts | Subsetting a time series |
summary.forecast | Forecasting time series |
summary.mforecast | Forecasting time series |
taperedacf | (Partial) Autocorrelation and Cross-Correlation Function Estimation |
taperedpacf | (Partial) Autocorrelation and Cross-Correlation Function Estimation |
taylor | Half-hourly electricity demand |
tbats | TBATS model (Exponential smoothing state space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components) |
tbats.components | Extract components of a TBATS model |
thetaf | Theta method forecast |
tsclean | Identify and replace outliers and missing values in a time series |
tsdisplay | Time series display |
tslm | Fit a linear model with time series components |
tsoutliers | Identify and replace outliers in a time series |
wineind | Australian total wine sales |
woolyrnq | Quarterly production of woollen yarn in Australia |