@article { author = {ALAMUTI, A. Y. and MESHKANI, R.}, title = {REGRESSION ANALYSIS IN MARKOV CHAIN}, journal = {Iranian Journal of Science}, volume = {30}, number = {3}, pages = {349-354}, year = {2006}, publisher = {Springer}, issn = {2731-8095}, eissn = {2731-8109}, doi = {10.22099/ijsts.2006.2774}, abstract = {In a finite stationary Markov chain, transition probabilities may depend on some explanatoryvariables. A similar problem has been considered here. The corresponding posteriors are derived andinferences are done using these posteriors. Finally, the procedure is illustrated with a real example.}, keywords = {Bayes,Empirical Bayes,estimation,Markov chain,maximum likelihood,Regression,transition probability matrix}, url = {https://ijsts.shirazu.ac.ir/article_2774.html}, eprint = {https://ijsts.shirazu.ac.ir/article_2774_087e665a3f96c6b1a75ad8e9d51a35a1.pdf} }