A time series taxonomy to classify univariate or multivariate time series based on either 24 or 15 different (statistical) time series features. The different taxonomy versions can be selected by the taxonomy_type parameter from the function 'classify_ts' of this package. It generates and collects all feature values. Next the feature values are scaled to [0,1] and then assigned to the defined taxonomy factors. Additionally, each feature can be calculated for it's own.
# Initialize the R package
library(tstaxonomyr)
# Example of the TS taxonomy classification --------
# Use the univariate time series object 'BJsales'
ts_sales = datasets::BJsales
# Classify the time series based on the defined taxonomy
# in 'classify_ts'
classified_ts <- classify_ts(ts = ts_sales,
na_option = "mean", taxonomy_type = "v1")
# Get the classification factor results
classified_ts
# Example of a single feature value calculation --------
# Calculate the skewness of a time series object
skewness = calculate_skewness(ts = ts_sales)
# Get the resulting skewness factor
skewness
You can install the development version 1.0.0 from Github with:
devtools::install_github("mowomoyela/tstaxonomyr")
All provided functions of this package:
This package is free and open source software, licensed under GPL-2.
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