Model-Based Clustering of Categorical Sequences
Dataset: result of backward state selection
Backward search for equivalent states
Dataset: simulated dataset
Model-based clustering of categorical sequences
EM algorithm for mixtures of Markov models
Plot of the obtained clustering solution
Forward search for equivalent states
Prediction of future state visits
Functions for Printing or Summarizing Objects
Reading sequences of visited states
Simulating sequences of visited states
Variance-covariance matrix estimation
Clustering categorical sequences by means of finite mixtures with Markov model components is the main utility of ClickClust. The package also allows detecting blocks of equivalent states by forward and backward state selection procedures.