Package index • feasts

Overview
`feasts` `feasts-package`	feasts: Feature Extraction and Statistics for Time Series
Graphics Graphics capabilities in feasts have moved to the ggtime package. Please use `library(ggtime)` in your code in order to continue using the `gg_*()` and `autoplot()` functions previously provided by this package.
Decompositions Useful for decomposing a time series into some simpler structural components.
`classical_decomposition()`	Classical Seasonal Decomposition by Moving Averages
`STL()`	Multiple seasonal decomposition by Loess
`generate(<stl_decomposition>)`	Generate block bootstrapped series from an STL decomposition
`X_13ARIMA_SEATS()`	X-13ARIMA-SEATS Seasonal Adjustment
Autocorrelation analysis Identify autocorrelations in the data.
`ACF()` `PACF()` `CCF()`	(Partial) Autocorrelation and Cross-Correlation Function Estimation
`feat_acf()`	Autocorrelation-based features
`feat_pacf()`	Partial autocorrelation-based features
Unit root tests Unit root tests for use with `fabletools::features()`.
`unitroot_kpss()` `unitroot_pp()`	Unit root tests
`unitroot_ndiffs()` `unitroot_nsdiffs()`	Number of differences required for a stationary series
Portmanteau tests Statistical tests for examining the null hypothesis of independence in a given time series.
`ljung_box()` `box_pierce()` `portmanteau_tests`	Portmanteau tests
Cointegration tests Statistical tests for investigating cointegration between time series.
`cointegration_johansen()`	Johansen Procedure for VAR
`cointegration_phillips_ouliaris()`	Phillips and Ouliaris Cointegration Features
Tiling window features Computes feature of a time series based on tiled (non-overlapping) windows.
`var_tiled_var()` `var_tiled_mean()`	Time series features based on tiled windows
Sliding window features Computes feature of a time series based on sliding (overlapping) windows.
`shift_level_max()` `shift_var_max()` `shift_kl_max()`	Sliding window features
Other features Uncategorised features
`feat_stl()`	STL features
`feat_spectral()`	Spectral features of a time series
`feat_intermittent()`	Intermittency features
`stat_arch_lm()`	ARCH LM Statistic
`n_crossing_points()`	Number of crossing points
`longest_flat_spot()`	Longest flat spot length
`coef_hurst()`	Hurst coefficient
`guerrero()`	Guerrero's method for Box Cox lambda selection

Reference

Overview

Graphics

Decompositions

Autocorrelation analysis

Unit root tests

Portmanteau tests

Cointegration tests

Tiling window features

Sliding window features

Other features