Number of differences required for a stationary series
Exponential smoothing forecasts
TBATS model (Exponential smoothing state space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components)
ARIMA errors
Forecasting using stl objects
Diebold-Mariano test for predictive accuracy
Fit ARIMA model to univariate time series
BATS model (Exponential smoothing state space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components)
Cubic Spline Forecast
Subsetting a time series
Forecasting using Holt-Winters objects
Forecasting using ETS models
Forecast a linear model with possible time series components
Naive forecasts
Multi-Seasonal Time Series
Seasonal plot
Seasonal dummy variables
Fit a fractionally differenced ARFIMA model
Double-Seasonal Holt-Winters Forecasting
Number of days in each season
Interpolate missing values in a time series
Forecast plot
Random Walk Forecast
Half-hourly electricity demand
Accuracy measures for forecast model
Forecasting using Structural Time Series models
Simulation from a time series model
One-step in-sample forecasts using ARIMA models
Cross-validation statistic
Moving-average smoothing
Australian monthly gas production
Forecasting time series
Daily morning gold prices
Forecasting using BATS and TBATS models
Fit best ARIMA model to univariate time series
Forecast seasonal index
Exponential smoothing state space model
Australian total wine sales
Fit a linear model with time series components
Time series display
(Partial) Autocorrelation Function Estimation
Box Cox Transformation
Log-Likelihood of an ets object
Seasonal adjustment
Mean Forecast
Theta method forecast
Automatic selection of Box Cox transformation parameter
Quarterly production of woollen yarn in Australia
Forecasts for intermittent demand using Croston's method
Forecasting using ARIMA or ARFIMA models
Plot components from ETS model