In a finite stationary Markov chain, transition probabilities may depend on some explanatory variables. A similar problem has been considered here. The corresponding posteriors are derived and inferences are done using these posteriors. Finally, the procedure is illustrated with a real example.
ALAMUTI, A. Y. and MESHKANI, R. (2006). REGRESSION ANALYSIS IN MARKOV CHAIN. Iranian Journal of Science, 30(3), 349-354. doi: 10.22099/ijsts.2006.2774
MLA
ALAMUTI, A. Y. , and MESHKANI, R. . "REGRESSION ANALYSIS IN MARKOV CHAIN", Iranian Journal of Science, 30, 3, 2006, 349-354. doi: 10.22099/ijsts.2006.2774
HARVARD
ALAMUTI, A. Y., MESHKANI, R. (2006). 'REGRESSION ANALYSIS IN MARKOV CHAIN', Iranian Journal of Science, 30(3), pp. 349-354. doi: 10.22099/ijsts.2006.2774
CHICAGO
A. Y. ALAMUTI and R. MESHKANI, "REGRESSION ANALYSIS IN MARKOV CHAIN," Iranian Journal of Science, 30 3 (2006): 349-354, doi: 10.22099/ijsts.2006.2774
VANCOUVER
ALAMUTI, A. Y., MESHKANI, R. REGRESSION ANALYSIS IN MARKOV CHAIN. Iranian Journal of Science, 2006; 30(3): 349-354. doi: 10.22099/ijsts.2006.2774