Box Cox Transformation
Create a ggplot layer appropriate to a particular data type
Forecasts for intermittent demand using Croston's method
Diebold-Mariano test for predictive accuracy
Forecasting time series
Forecasting using Structural Time Series models
Create a seasonal subseries ggplot
Daily morning gold prices
Multi-Seasonal Time Series
Interpolate missing values in a time series
Plot components from BATS model
Plot components from ETS model
Theta method forecast
Time series cross-validation
Australian total wine sales
Quarterly production of woollen yarn in Australia
ggplot (Partial) Autocorrelation and Cross-Correlation Function Estimation
and Plotting
Plot time series decomposition components using ggplot
Forecasting using ARIMA or ARFIMA models
Fit a fractionally differenced ARFIMA model
Accuracy measures for a forecast model
Forecasting using Holt-Winters objects
Forecasting using the bagged ETS method
Forecasting using BATS and TBATS models
Histogram with optional normal and kernel density functions
Time series lag ggplots
Neural Network Time Series Forecasts
Plot characteristic roots from ARIMA model
Objects exported from other packages
Residuals for various time series models
TBATS model (Exponential smoothing state space model with Box-Cox
transformation, ARMA errors, Trend and Seasonal components)
Extract components of a TBATS model
Identify and replace outliers and missing values in a time series
Time series display
(Partial) Autocorrelation and Cross-Correlation Function Estimation
Fit ARIMA model to univariate time series
BATS model (Exponential smoothing state space model with Box-Cox
transformation, ARMA errors, Trend and Seasonal components)
Number of trading days in each season
Double-Seasonal Holt-Winters Forecasting
Easter holidays in each season
Forecast a multiple linear model with possible time series components
Forecasting time series
Fourier terms for modelling seasonality
Australian monthly gas production
Mean Forecast
Number of days in each season
Seasonal dummy variables
Seasonal plot
Subsetting a time series
Half-hourly electricity demand
Return the order of an ARIMA or ARFIMA model
Errors from a regression model with ARIMA errors
Check that residuals from a time series model look like white noise
Box-Cox and Loess-based decomposition bootstrap.
h-step in-sample forecasts for time series models.
Forecasting Functions for Time Series and Linear Models
Automatically create a ggplot for time series objects
Forecasting using the bagged ETS method
k-fold Cross-Validation applied to an autoregressive model
Cross-validation statistic
Forecasting using ETS models
Exponential smoothing state space model
Forecast a linear model with possible time series components
Is an object constant?
Find dominant frequency of a time series
Is an object a particular model type?
Is an object a particular forecast type?
Moving-average smoothing
Forecasting using stl objects
Forecast plot
Forecast plot
Forecasting using neural network models
Get response variable from time series model.
Multivariate forecast plot
Exponential smoothing forecasts
Naive and Random Walk Forecasts
Number of differences required for a stationary series
Simulation from a time series model
Fit a linear model with time series components
Identify and replace outliers in a time series
Seasonal adjustment
Extract components from a time series decomposition
Forecast seasonal index
Cubic Spline Forecast
Automatic selection of Box Cox transformation parameter
Fit best ARIMA model to univariate time series