In this paper, we study a model of hypotheses testing consisting of two simple homogeneous stationary Markov chains with a finite number of states such that having different distributions from L≥ 2 possible transition probabilities. The matrix of all possible pairs of asymptotical interdependence of the error probability exponents for logarithmically asymptotically optimal testing is determined. For this aim, we apply the method of type and large deviation techniques.
Akbari, R., & Navaei, L. (2022). On General Case of Universal Hypothesis Optimal Testing for L ≥ 2 Differently Distributed for Markov Chains. Journal of Statistical Modelling: Theory and Applications, 3(1), 51-60. doi: 10.22034/jsmta.2023.18808.1061
MLA
Reza Akbari; Leader Navaei. "On General Case of Universal Hypothesis Optimal Testing for L ≥ 2 Differently Distributed for Markov Chains", Journal of Statistical Modelling: Theory and Applications, 3, 1, 2022, 51-60. doi: 10.22034/jsmta.2023.18808.1061
HARVARD
Akbari, R., Navaei, L. (2022). 'On General Case of Universal Hypothesis Optimal Testing for L ≥ 2 Differently Distributed for Markov Chains', Journal of Statistical Modelling: Theory and Applications, 3(1), pp. 51-60. doi: 10.22034/jsmta.2023.18808.1061
VANCOUVER
Akbari, R., Navaei, L. On General Case of Universal Hypothesis Optimal Testing for L ≥ 2 Differently Distributed for Markov Chains. Journal of Statistical Modelling: Theory and Applications, 2022; 3(1): 51-60. doi: 10.22034/jsmta.2023.18808.1061
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