A five-state hidden Markov model (HMM) fitted for the biofam
data.
A hidden Markov model of class hmm
;
a left-to-right model with four hidden states.
The model is loaded by calling data(hmm_biofam)
. It was created with the
following code:
data("biofam3c")# Building sequence objects
marr_seq <- seqdef(biofam3c$married, start = 15,
alphabet = c("single", "married", "divorced"))
child_seq <- seqdef(biofam3c$children, start = 15,
alphabet = c("childless", "children"))
left_seq <- seqdef(biofam3c$left, start = 15,
alphabet = c("with parents", "left home"))
## Choosing colors
attr(marr_seq, "cpal") <- c("violetred2", "darkgoldenrod2", "darkmagenta")
attr(child_seq, "cpal") <- c("darkseagreen1", "coral3")
attr(left_seq, "cpal") <- c("lightblue", "red3")
init <- c(0.9, 0.05, 0.02, 0.02, 0.01)
# Starting values for transition matrix
trans <- matrix(
c(0.8, 0.10, 0.05, 0.03, 0.02,
0, 0.9, 0.05, 0.03, 0.02,
0, 0, 0.9, 0.07, 0.03,
0, 0, 0, 0.9, 0.1,
0, 0, 0, 0, 1),
nrow = 5, ncol = 5, byrow = TRUE)
# Starting values for emission matrices
emiss_marr <- matrix(
c(0.9, 0.05, 0.05, # High probability for single
0.9, 0.05, 0.05,
0.05, 0.9, 0.05, # High probability for married
0.05, 0.9, 0.05,
0.3, 0.3, 0.4), # mixed group
nrow = 5, ncol = 3, byrow = TRUE)
emiss_child <- matrix(
c(0.9, 0.1, # High probability for childless
0.9, 0.1,
0.1, 0.9,
0.1, 0.9,
0.5, 0.5),
nrow = 5, ncol = 2, byrow = TRUE)
emiss_left <- matrix(
c(0.9, 0.1, # High probability for living with parents
0.1, 0.9,
0.1, 0.9,
0.1, 0.9,
0.5, 0.5),
nrow = 5, ncol = 2, byrow = TRUE)
initmod <- build_hmm(
observations = list(marr_seq, child_seq, left_seq),
initial_probs = init, transition_probs = trans,
emission_probs = list(emiss_marr, emiss_child,
emiss_left),
channel_names = c("Marriage", "Parenthood", "Residence"))
fit_biofam <- fit_model(initmod, em = FALSE, local = TRUE)
hmm_biofam <- fit_biofam$model
Examples of building and fitting HMMs in build_hmm
and
fit_model
; and biofam
for the original data and
biofam3c
for the three-channel version used in this model.
# Plotting the model
plot(hmm_biofam)
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