| 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]