hmm-fwbk {stochmod} | R Documentation |
Forward-Backward procedure
HMM.fwbk( x, hmm )
x |
[N x p] matrix of N samples in p dimensions |
hmm |
An HMM |
The E-step of the EM algorithm for Hidden Markov Models
alpha |
[N x K] matrix of forward variable values |
beta |
[N x K] matrix of backward variable values |
c |
[N x 1] vector of scaling coefficients |
gamma |
[N x K] matrix of transition probabilities from state i: gamma[t,i] = P( Qt = i | O,hmmp ) |
xi |
[N-1 x K x K] array of transition probabilties from state i to state j: xi[t,i,j] = P( Qt = i, Qt+1 = j | O,hmmp ) |
Artem Sokolov Artem.Sokolov@gmail.com