Classification of Demographic Sequences Using Hidden Markov Models

Student: Stepanyuk Irina

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Year of Graduation: 2017

This paper focuses on the sequence classification in terms of the analysis of life course trajectories. We propose a model-based approach that utilizes Hidden Markov models in order to classify sequences. Moreover, a preprocessing of sequences, that permits to utilize conventional classification methods, is considered. Proposed approaches are compared with other classification methods. In this study we pointed out the relevance of a model-based approach for life course studies. Moreover, based on the results some conclusions were drawn about differences in demographic behavior. This knowledge is urgent and can be of interest to demographers.

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