scholarly journals A Dependent Hidden Markov Model of Credit Quality

2012 ◽  
Vol 2012 ◽  
pp. 1-13 ◽  
Author(s):  
Małgorzata Wiktoria Korolkiewicz
Keyword(s):  
Markov Chain ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Credit Rating ◽  
Hidden Markov ◽  
Credit Ratings ◽  
The State ◽  
Credit Quality ◽  
The Em Algorithm ◽  
Rating Process

We propose a dependent hidden Markov model of credit quality. We suppose that the "true" credit quality is not observed directly but only through noisy observations given by posted credit ratings. The model is formulated in discrete time with a Markov chain observed in martingale noise, where "noise" terms of the state and observation processes are possibly dependent. The model provides estimates for the state of the Markov chain governing the evolution of the credit rating process and the parameters of the model, where the latter are estimated using the EM algorithm. The dependent dynamics allow for the so-called "rating momentum" discussed in the credit literature and also provide a convenient test of independence between the state and observation dynamics.

scholarly journals Research on identification method of heavy vehicle rollover based on hidden Markov model

Open Physics ◽  
2017 ◽  
Vol 15 (1) ◽  
pp. 479-485 ◽  
Author(s):  
Zhiguo Zhao ◽  
Yeqin Wang ◽  
Xiaoming Hu ◽  
Yukai Tao ◽  
Jinsheng Wang
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Early Warning ◽  
Hidden Markov ◽  
The State ◽  
Lateral Acceleration ◽  
Heavy Vehicle ◽  
General Strategy ◽  
Identification Method ◽  
Vehicle Rollover

AbstractAiming at the problem of early warning credibility degradation as the heavy vehicle load and its center of gravity change greatly; the heavy vehicle rollover state identification method based on the Hidden Markov Model (HMM, is introduced to identify heavy vehicle lateral conditions dynamically in this paper. In this method, the lateral acceleration and roll angle are taken as the observation values of the model base. The Viterbi algorithm is used to predict the state sequence with the highest probability in the observed sequence, and the Markov prediction algorithm is adopted to calculate the state transition law and to predict the state of the vehicle in a certain period of time in the future. According to combination conditions of Double lane change and steering, applying Trucksim and Matlab trained hidden Markov model, the model is applied to the online identification of heavy vehicle rollover states. The identification results show that the model can accurately and efficiently identify the vehicle rollover state, and has good applicability. This study provides a novel method and a general strategy for active safety early warning and control of vehicles, which has reference significance for the application of the Hidden Markov theory in collision, rear-end and lane departure warning system.

scholarly journals Text segmentation by language

2016 ◽  
Vol 14 (38) ◽  
pp. 63-72 ◽  
Author(s):  
Robin Cabeza Ruiz
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Hidden Markov ◽  
The State ◽  
Text Segmentation ◽  
State Of Art

There are two approaches for text segmentation by language: first, assuming that language changes happen in the “border” between sentences (never within a sentence); second, assuming that language changes can happen anyplace in the text. This work presents methods for both types of text’s segmentation by languages. On the first proposal, the text is initially segmented by sentence, then the language of each sentence is obtained; the second proposal is an adaptation of hidden Markov model to this task. Both cases, according to results obtained in experimental proofs, exceed the state of art.

Sign in / Sign up

Export Citation Format

Share Document