Estimating the Order of Markov Chains Using Shannon Criterion and Akaike Criterion
DOI:
https://doi.org/10.62933/kev7nx24Keywords:
Markov Chain , Order Estimation, Prediction , Markov ProcessesAbstract
Determining the order of a Markov chain is un important problem, as the correct decision to be made will be based on the specific order of that model. This research involves a Markov chain analysis of the gene sequence for the breast cancer-causing gene (BRCA1) and estimating its order using Shannon's Information Criterion and Akaike's Information Criteria. Selecting the appropriate order in modeling contributes to enhancing the understanding of the behavior of genes associated with breast cancer and enables early detection and the development of effective treatment strategies. The two aforementioned criteria were used, and the results showed that the order of this gene is the Second order using Shannon's criterion, and the Second -order model is the most accurate using Akaike's criteria.
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