Analyzing Categorical Time Series
Constructs the binarized time series associated with a given categoric...
Computes several features associated with a categorical time series
Computes the relative frequency of motifs in a categorical time series
Computes several subfeatures associated with a categorical time series
Computes the conditional probabilities of a categorical time series
Computes the joint probabilities of a categorical time series
Computes the marginal probabilities of a categorical time series
Constructs a control chart for the cycle lengths of a categorical seri...
Constructs a serial dependence plot based on Cohen's kappa
Constructs a serial dependence plot based on Cramer's vi
Constructs a categorical time series plot
Constructs the IFS circle transformation of a categorical time series
Constructs a control chart for the marginal distribution of a categori...
Constructs the pattern histogram associated with a given category of a...
Constructs the rate evolution graph for a categorical time series
Represents the spectral envelope of a categorical time series
An implementation of several functions for feature extraction in categorical time series datasets. Specifically, some features related to marginal distributions and serial dependence patterns can be computed. These features can be used to feed clustering and classification algorithms for categorical time series, among others. The package also includes some interesting datasets containing biological sequences. Practitioners from a broad variety of fields could benefit from the general framework provided by 'ctsfeatures'.