predict.hmm {mhsmm} | R Documentation |
Predicts the underlying state sequence for an observed sequence x
given a hmm
model
## S3 method for class 'hmm': predict(object, x,method = "viterbi", ...)
object |
An object of class hmm |
x |
A vector or data.frame of observations |
method |
Prediction method (see details) |
... |
further arguments passed to or from other methods. |
If method="viterbi"
, this technique applies the Viterbi algorithm for HMMs, producing the most likely sequence of states given the observed data. If method="smoothed"
, then the individually most likely (or smoothed) state sequence is produced, along with a matrix witht the respective probabilities for each state.
Returns a hsmm.data
object, suitable for plotting.
x |
A vector or data.frame of observations |
s |
A vector containing the reconstructed state sequence |
N |
The lengths of each sequence |
p |
A matrix where the rows represent time steps and the columns are the probability for the respective state (only produced when method="smoothed" ) |
Jared O'Connell
Rabiner, L. (1989), A tutorial on hidden Markov models and selected applications in speech recognition, Proceedings of the IEEE, 77, 257-286.
hmm
##See examples in 'hmm'