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The 21st century has witnessed a growing interest in the analysis of timeseries data. Whereas most of the literature on the topic deals with real-valuedtime series, ordinal time series have typically received much less attention.However, the development of specific analytical tools for the latter objectshas substantially increased in recent years. The R package otsfeatures attemptsto provide a set of simple functions for analyzing ordinal time series. Inparticular, several commands allowing the extraction of well-known statisticalfeatures and the execution of inferential tasks are available for the user. Theoutput of several functions can be employed to perform traditional machinelearning tasks including clustering, classification or outlier detection.otsfeatures also incorporates two datasets of financial time series which wereused in the literature for clustering purposes, as well as three interestingsynthetic databases. The main properties of the package are described and itsuse is illustrated through several examples. Researchers from a broad varietyof disciplines could benefit from the powerful tools provided by otsfeatures.

Ordinal time series analysis with the R package otsfeatures