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