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