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my_hdr
2011 Jan 26
0
hmm.discnp hidden markov model
...-90, -84, -77, -75, -64, -60, -58, -55, -56, -57,
-57, -63, -77, -81, -82, -91, -85, -89, -93)
quant <- length(-110:-6)
# Initialize and train the hmm with the observed sequence mentioned above.
# "yval" lists the possible values for observations and K is the number of
hidden states.
my_hmm <- hmm(y=signature, yval=c(-110:-6), K=5)
print(my_hmm)
The above shows that the HMM was trained using "signature" and the values
seem to be intuitive.
My question is more a fundamental one in regards to understanding HMMs. I
know I should use more examples of the above sequences...