# How to calculate a probability of a sequence of observations in Hidden Markov Model?

Given a model (from Ankur Jain's slides) and question with the answer is presented below:

Initial probabilities: say P(‘Low’)=0.4 , P(‘High’)=0.6 .

However i'm confused why in the solution we have an extra 0.4, i guess it should be as follows, can you clarify me?

P(‘Dry’|’Low’)P(‘Rain’|’Low’) P(‘Low’)P(‘Low’|’Low)
= 0.4*0.6*0.4*0.3

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It looks like your calculation is correct, unless I'm also missing something. –  VitalStatistix Jan 8 '13 at 12:58
@VitalStatistix, thanks i guess so if not whole of my code will give wrong result –  berkay Jan 8 '13 at 13:17