The interacting multiple model algorithm based on adaptive Markov transition probability

2017 ◽  
Author(s):  
Du Ming-yang ◽  
Bi Da-ping ◽  
Wang Shu-liang
Keyword(s):  
Transition Probability ◽  
Interacting Multiple Model ◽  
Multiple Model ◽  
Markov Transition Probability ◽  
Markov Transition ◽  
Model Algorithm

Interacting multiple model algorithm based on joint likelihood estimation

2011 ◽  
Vol 28 (4-6) ◽  
pp. 427-432
Author(s):  
Jie Sun ◽  
Chaoshu Jiang ◽  
Zhuming Chen ◽  
Wei Zhang
Keyword(s):  
Likelihood Estimation ◽  
Interacting Multiple Model ◽  
Multiple Model ◽  
Joint Likelihood ◽  
Model Algorithm

scholarly journals On the evolution of corruption patterns in the post-communist countries

Equilibrium ◽  
2015 ◽  
Vol 10 (1) ◽  
pp. 33 ◽  
Author(s):  
Andrzej Cieślik ◽  
Łukasz Goczek
Keyword(s):  
Transition Probability ◽  
Transition Probability Matrix ◽  
Markov Transition Probability ◽  
Long Run ◽  
Markov Transition ◽  
Corruption Index ◽  
Communist Countries ◽  
Control Of Corruption ◽  
Over Time

In this paper, we study the evolution of corruption patterns in 27 post-communist countries during the period 1996-2012 using the Control of Corruption Index and the corruption category Markov transition probability matrix. This method allows us to generate the long-run distribution of corruption among the post-communist countries. Our empirical findings suggest that corruption in the post-communist countries is a very persistent phenomenon that does not change much over time. Several theoretical explanations for such a result are provided.

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