Calculate conditional local state probabilities for inhomogeneous HMMs
stateprobs_g.Rd
Computes $$\Pr(S_t = j \mid X_1, ..., X_T)$$ for inhomogeneous HMMs
Arguments
- delta
initial or stationary distribution of length N, or matrix of dimension c(k,N) for k independent tracks, if
trackID
is provided- 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) for a single track is provided, the first slice will be ignored.
If
trackID
is provided,Gamma
needs to be an array of dimension c(N,N,n), where n is the number of rows inallprobs
. Then for each track the first transition matrix will be ignored.- 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_g
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_p()
,
viterbi()
,
viterbi_g()
,
viterbi_p()