mowomoyela/tstaxonomyr: A time series taxonomy to classify univariate or multivariate time series

A time series taxonomy to classify univariate or multivariate time series based on 24 different (statistical) time series features: number_of_observations", "number_of_attributes", "coefficient of determination", "durbin watson test", "mean", "periodicity", "chaos", "entropy", "selfsimilarity", "dynamic time warping (DTW) distance ", "percentage of turning points", "variance", "percentage of outliers", "percentage of step changes", "quartile distribition", "standard deviation", "percentage of peaks", "trend", "seasonality", "autocorrelation", "partial autocorrelation", "skewness", "kurtosis", "non linearity" Also, each feature can be calculated for it own. But the overall taxonomy function of the package 'classify_ts' collects all feature values and scales them to [0,1] and then assign them to the defined taxonomy factors.

install.packages("remotes")
remotes::install_github("mowomoyela/tstaxonomyr")