viterbi function

Viterbi algorithm for state decoding in homogeneous HMMs

The Viterbi algorithm allows one to decode the most probable state sequence of an HMM.

viterbi(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 trackID is provided

• Gamma: transition probability matrix of dimension c(N,N) or array of transition probability matrices of dimension c(N,N,k) if trackID is provided

• 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 delta, transition probability matrix Gamma, matrix of state-dependent probabilities allprobs, and potentially a trackID variable

  If you are using automatic differentiation either with RTMB::MakeADFun or qreml and include forward in your likelihood function, the objects needed for state decoding are automatically reported after model fitting. Hence, you can pass the model object obtained from running RTMB::report() or from qreml directly to this function.

Returns

vector of decoded states of length n

Examples

delta = c(0.5, 0.5)
Gamma = matrix(c(0.9, 0.1, 0.2, 0.8), nrow = 2, byrow = TRUE)
allprobs = matrix(runif(200), nrow = 100, ncol = 2)
states = viterbi(delta, Gamma, allprobs)

See Also

Other decoding functions: stateprobs(), stateprobs_g(), stateprobs_p(), viterbi_g(), viterbi_p()