A parallel filtered-based EM algorithm for hidden Markov model and sinusoidal drift parameter estimation with systolic array implementation

2002 ◽  
Author(s):  
V. Krishnamurthy ◽  
R.J. Elliott
Keyword(s):  
Parameter Estimation ◽  
Markov Model ◽  
Em Algorithm ◽  
Hidden Markov Model ◽  
Systolic Array ◽  
Hidden Markov ◽  
Drift Parameter

scholarly journals Confidence Intervals for the Mixture Transition Distribution (MTD) Model and Other Markovian Models

Symmetry ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 351
Author(s):  
André Berchtold
Keyword(s):  
Markov Chains ◽  
Markov Model ◽  
Em Algorithm ◽  
Hidden Markov Model ◽  
Confidence Intervals ◽  
Hidden Markov ◽  
Simple Calculation ◽  
Standard Methods ◽  
Transition Distribution ◽  
Simulation Results

The Mixture Transition Distribution (MTD) model used for the approximation of high-order Markov chains does not allow a simple calculation of confidence intervals, and computationnally intensive methods based on bootstrap are generally used. We show here how standard methods can be extended to the MTD model as well as other models such as the Hidden Markov Model. Starting from existing methods used for multinomial distributions, we describe how the quantities required for their application can be obtained directly from the data or from one run of the E-step of an EM algorithm. Simulation results indicate that when the MTD model is estimated reliably, the resulting confidence intervals are comparable to those obtained from more demanding methods.

Sign in / Sign up

Export Citation Format

Share Document