simulate_initial_probs {seqHMM} | R Documentation |
Simulate Parameters of Hidden Markov Models
Description
These are helper functions for quick construction of initial values for various model building functions. Mostly useful for global optimization algorithms which do not depend on initial values.
Usage
simulate_initial_probs(n_states, n_clusters = 1, alpha = 1)
simulate_transition_probs(
n_states,
n_clusters = 1,
left_right = FALSE,
diag_c = 0,
alpha = 1
)
simulate_emission_probs(n_states, n_symbols, n_clusters = 1, alpha = 1)
Arguments
n_states |
Number of states in each cluster. |
n_clusters |
Number of clusters. |
alpha |
A scalar, or a vector of length S (number of states) or M (number of symbols) defining the parameters of the Dirichlet distribution used to simulate the probabilities. |
left_right |
Constrain the transition probabilities to upper triangular.
Default is |
diag_c |
A constant value to be added to diagonal of transition matrices before scaling. |
n_symbols |
Number of distinct symbols in each channel. |
[Package seqHMM version 2.0.0 Index]