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