viterbi_g {LaMa} | R Documentation |
Viterbi algorithm for state decoding in inhomogeneous HMMs
Description
The Viterbi algorithm allows one to decode the most probable state sequence of an HMM.
Usage
viterbi_g(delta, Gamma, allprobs, trackID = NULL, mod = NULL)
Arguments
delta |
initial distribution of length N, or matrix of dimension c(k,N) for k independent tracks, if |
Gamma |
array of transition probability matrices of dimension c(N,N,n-1), as in a time series of length n, there are only n-1 transitions If an array of dimension c(N,N,n) is provided for a single track, the first slice will be ignored. If |
allprobs |
matrix of state-dependent probabilities/ density values of dimension c(n, N) |
trackID |
optional vector of k track IDs, if multiple tracks need to be decoded separately |
mod |
optional model object containing initial distribution If you are using automatic differentiation either with |
Value
vector of decoded states of length n
See Also
Other decoding functions:
stateprobs()
,
stateprobs_g()
,
stateprobs_p()
,
viterbi()
,
viterbi_p()
Examples
delta = c(0.5, 0.5)
Gamma = tpm_g(runif(10), matrix(c(-2,-2,1,-1), nrow = 2))
allprobs = matrix(runif(20), nrow = 10, ncol = 2)
states = viterbi_g(delta, Gamma[,,-1], allprobs)