Description Usage Arguments Value See Also Examples

`obtain_emiss`

obtains the emission distribution probabilities (also
known as conditional probabilities) for a fitted multilevel hidden Markov
model, for either the group level, i.e., representing the average emission
distribution probabilities over all subjects, or at the subject level,
returning the emission distribution probabilities for each subject.

1 | ```
obtain_emiss(object, level = "group", burn_in = NULL)
``` |

`object` |
An object of class |

`level` |
String specifying if the returned emission distribution
probabilities should be at the group level ( |

`burn_in` |
An integer which specifies the number of iterations to discard
when obtaining the model parameter summary statistics. When left
unspecified ( |

`obtain_emiss`

returns the object `est_emiss`

. Depending on
the specification at the input variable `level`

, `est_emiss`

is
either a list of matrices with the emission distribution probabilities at
the group level (if `level = "group"`

) for each dependent variable, or
a list of lists, where for each dependent variable a list is returned with
the number of elements equal to the number of subjects analyzed, if
`level = 'subject'`

). In the latter scenario, each matrix in the lower
level list represents the subject specific emission distribution
probabilities for a specific dependent variable.

`mHMM`

for fitting the multilevel hidden Markov
model, creating the object `mHMM`

.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | ```
###### Example on package data
# specifying general model properties:
m <- 2
n_dep <- 4
q_emiss <- c(3, 2, 3, 2)
# specifying starting values
start_TM <- diag(.8, m)
start_TM[lower.tri(start_TM) | upper.tri(start_TM)] <- .2
start_EM <- list(matrix(c(0.05, 0.90, 0.05,
0.90, 0.05, 0.05), byrow = TRUE,
nrow = m, ncol = q_emiss[1]), # vocalizing patient
matrix(c(0.1, 0.9,
0.1, 0.9), byrow = TRUE, nrow = m,
ncol = q_emiss[2]), # looking patient
matrix(c(0.90, 0.05, 0.05,
0.05, 0.90, 0.05), byrow = TRUE,
nrow = m, ncol = q_emiss[3]), # vocalizing therapist
matrix(c(0.1, 0.9,
0.1, 0.9), byrow = TRUE, nrow = m,
ncol = q_emiss[4])) # looking therapist
# Run a model without covariate(s):
out_2st <- mHMM(s_data = nonverbal,
gen = list(m = m, n_dep = n_dep, q_emiss = q_emiss),
start_val = c(list(start_TM), start_EM),
mcmc = list(J = 11, burn_in = 5))
out_2st
summary(out_2st)
# obtaining the emission probabilities at the group and subject level
obtain_emiss(out_2st, level = "group")
obtain_emiss(out_2st, level = "subject")
``` |

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