Feature Extraction and Statistics for Time Series

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Documentation for package ‘feasts’ version 0.3.2

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feasts-package feasts: Feature Extraction and Statistics for Time Series
ACF (Partial) Autocorrelation and Cross-Correlation Function Estimation
autoplot.tbl_cf Auto- and Cross- Covariance and -Correlation plots
box_pierce Portmanteau tests
CCF (Partial) Autocorrelation and Cross-Correlation Function Estimation
classical_decomposition Classical Seasonal Decomposition by Moving Averages
coef_hurst Hurst coefficient
feasts feasts: Feature Extraction and Statistics for Time Series
feat_acf Autocorrelation-based features
feat_intermittent Intermittency features
feat_pacf Partial autocorrelation-based features
feat_spectral Spectral features of a time series
feat_stl STL features
generate.stl_decomposition Generate block bootstrapped series from an STL decomposition
gg_arma Plot characteristic ARMA roots
gg_lag Lag plots
gg_season Seasonal plot
gg_subseries Seasonal subseries plots
gg_tsdisplay Ensemble of time series displays
gg_tsresiduals Ensemble of time series residual diagnostic plots
guerrero Guerrero's method for Box Cox lambda selection
ljung_box Portmanteau tests
longest_flat_spot Longest flat spot length
n_crossing_points Number of crossing points
n_flat_spots Longest flat spot length
PACF (Partial) Autocorrelation and Cross-Correlation Function Estimation
portmanteau_tests Portmanteau tests
shift_kl_max Sliding window features
shift_level_max Sliding window features
shift_var_max Sliding window features
stat_arch_lm ARCH LM Statistic
STL Multiple seasonal decomposition by Loess
unitroot_kpss Unit root tests
unitroot_ndiffs Number of differences required for a stationary series
unitroot_nsdiffs Number of differences required for a stationary series
unitroot_pp Unit root tests
var_tiled_mean Time series features based on tiled windows
var_tiled_var Time series features based on tiled windows
X_13ARIMA_SEATS X-13ARIMA-SEATS Seasonal Adjustment