Viterbi algorithm for state decoding in homogeneous HMMs
viterbi.Rd
The Viterbi algorithm allows one to decode the most probable state sequence of an HMM.
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 matrixGamma
, matrix of state-dependent probabilitiesallprobs
, and potentially atrackID
variableIf you are using automatic differentiation either with
RTMB::MakeADFun
orqreml
and includeforward
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 runningRTMB::report()
or fromqreml
directly to this function.
See also
Other decoding functions:
stateprobs()
,
stateprobs_g()
,
stateprobs_p()
,
viterbi_g()
,
viterbi_p()