Difference between revisions of "CH391L/HiddenMarkovModel"
From Marcotte Lab
< CH391L
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** F -> L : 0.05 | ** F -> L : 0.05 | ||
** L -> L : 0.90 | ** L -> L : 0.90 | ||
− | ** L -> F : 0.10 | + | ** L -> F : 0.10 |
To be continued... | To be continued... |
Revision as of 00:03, 20 February 2011
Viterbi Algorithm
This is an 'dishonest casino' example from Durbin, et al. 'Biological Sequence Analysis' book. A casino used two types of dice: one is a 'fair' one that has equal chance to all six numbers, and the other is a 'loaded' one that has high chance of number 6 than the others. We have a sequence of dice numbers from the casino, and want to estimate when a dealer exchanged the dice.
We assume that the Hidden Markov Model of this example as below:
As you see, both emission probability and transition probability are given.
- [Emission probability]
- Fair: 1/6 1/6 1/6 1/6 1/6 1/6
- Loaded: 0.1 0.1 0.1 0.1 0.1 0.5
- [Transition probability]
- F -> F : 0.95
- F -> L : 0.05
- L -> L : 0.90
- L -> F : 0.10
To be continued...