process_hid_formulas: Process and standardise formulas for the state process of...

In LaMa: Fast Numerical Maximum Likelihood Estimation for Latent Markov Models

Process and standardise formulas for the state process of hidden Markov models

Description

Process and standardise formulas for the state process of hidden Markov models

Usage

process_hid_formulas(formulas, nStates, ref = NULL)

Arguments

formulas	formulas for the transition process of a hidden Markov model, either as a single formula, a list of formulas, or a matrix.
nStates	number of states of the Markov chain
ref	optional vector of reference categories for each state, defaults to 1:nStates. If provided, must be of length nStates and contain valid state indices. If a formula matrix is provided, this cannot be specified because reference categries are specified by one "." entry in each row.

Value

named list of formulas of length nStates * (nStates - 1), where each formula corresponds to a transition from state i to state j, excluding transitions from i to ref[i].

Examples

# single formula for all non-reference category elements
formulas = process_hid_formulas(~ s(x), nStates = 3)
# now a list of length 6 with names tr.ij, not including reference categories

# different reference categories
formulas = process_hid_formulas(~ s(x), nStates = 3, ref = c(1,1,1))

# different formulas for different entries (and only for 2 of 6)
formulas = list(tr.12 ~ s(x), tr.23 ~ s(y))
formulas = process_hid_formulas(formulas, nStates = 3, ref = c(1,1,1))
# also a list of length 6, remaining entries filled with tr.ij ~ 1

# matrix input with reference categories
formulas = matrix(c(".", "~ s(x)", "~ s(y)",
                    "~ g", ".", "~ I(x^2)",
                    "~ y", "~ 1", "."), 
                    nrow = 3, byrow = TRUE)
# dots define reference categories
formulas = process_hid_formulas(formulas, nStates = 3)

LaMa documentation built on Nov. 5, 2025, 6:42 p.m.