select.seeds: Seed Selection Procedure

In DBHC: Sequence Clustering with Discrete-Output HMMs

Seed Selection Procedure

Description

Seed selection procedure of the DBHC algorithm, also invokes size search algorithm for seed in size.search. Used in hmm.clust.

Usage

select.seeds(
  sequences,
  log_space = FALSE,
  K,
  seed.size = 3,
  init.size = 2,
  print = FALSE,
  smoothing = 1e-04
)

Arguments

sequences	An stslist object (see seqdef) of sequences with discrete observations.
log_space	Logical, parameter provided to fit_model for whether to use optimization in log space or not.
K	The number of seeds to select, equal to the number of clusters in a partition.
seed.size	Seed size, the number of sequences to be selected for a seed.
init.size	The number of HMM states in an initial HMM.
print	Logical, whether to print intermediate steps or not.
smoothing	Smoothing parameter for absolute discounting in smooth.probabilities.

Value

A partition as a list object with HMMs for the selected seeds.

See Also

Used in main function for the DBHC algorithm hmm.clust.

DBHC documentation built on Dec. 28, 2022, 2:44 a.m.