hmm_biofam: Hidden Markov model for the biofam data

In helske/seqHMM: Mixture Hidden Markov Models for Social Sequence Data and Other Multivariate, Multichannel Categorical Time Series

Hidden Markov model for the biofam data

Description

A five-state hidden Markov model (HMM) fitted for the biofam data.

Format

A hidden Markov model of class hmm; a left-to-right model with four hidden states.

Details

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

See Also

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.

Examples

# Plotting the model
plot(hmm_biofam)

helske/seqHMM documentation built on July 6, 2023, 6:45 a.m.