posterior {tileHMM} | R Documentation |
For each state of an HMM the posterior probability that this state produced a given observation is calculated.
posterior(data, hmm, log = TRUE)
data |
Vector with observation sequence. |
hmm |
Object of class hmm . |
log |
Logical indicating whether the logarithm of the posterior probability should be returned. |
Regardless of the value of log
the computation is carried out in log space. If log = FALSE
the result is transformed back to linear space before it is returned.
A matrix with as many rows as hmm
has states and one column for each entry in data.
Peter Humburg
## create two state HMM with t distributions state.names <- c("one","two") transition <- c(0.1, 0.02) location <- c(1, 2) scale <- c(1, 1) df <- c(4, 6) model <- getHMM(list(a=transition, mu=location, sigma=scale, nu=df), state.names) ## obtain observation sequence from model obs <- sampleSeq(model, 100) ## calculate posterior probability for state "one" post <- posterior(obs, model, log=FALSE) ## get sequence of individually most likely states state.seq <- apply(post,2,max) state.seq <- states(model)[state.seq]