Feature Extraction and Statistics for Time Series
(Partial) Autocorrelation and Cross-Correlation Function Estimation
Auto- and Cross- Covariance and -Correlation plots
Classical Seasonal Decomposition by Moving Averages
Hurst coefficient
Johansen Procedure for VAR
Phillips and Ouliaris Cointegration Test
feasts: Feature Extraction and Statistics for Time Series
Autocorrelation-based features
Intermittency features
Partial autocorrelation-based features
Spectral features of a time series
STL features
Generate block bootstrapped series from an STL decomposition
Plot characteristic ARMA roots
Plot impulse response functions
Lag plots
Seasonal plot
Seasonal subseries plots
Ensemble of time series displays
Ensemble of time series residual diagnostic plots
Guerrero's method for Box Cox lambda selection
Longest flat spot length
Number of crossing points
Portmanteau tests
Objects exported from other packages
lagged datetime scales This set of scales defines new scales for lagge...
Sliding window features
ARCH LM Statistic
Multiple seasonal decomposition by Loess
Time series features based on tiled windows
Number of differences required for a stationary series
Unit root tests
X-13ARIMA-SEATS Seasonal Adjustment
Provides a collection of features, decomposition methods, statistical summaries and graphics functions for the analysing tidy time series data. The package name 'feasts' is an acronym comprising of its key features: Feature Extraction And Statistics for Time Series.
Useful links