logllk_lcm: Calculate loglikelihood of the latent class model,...

In ddtlcm: Latent Class Analysis with Dirichlet Diffusion Tree Process Prior

Calculate loglikelihood of the latent class model, conditional on tree structure

Description

Calculate loglikelihood of the latent class model, conditional on tree structure

Usage

logllk_lcm(
  response_matrix,
  leaf_data,
  prior_class_probability,
  prior_dirichlet,
  ClassItem,
  Class_count
)

Arguments

response_matrix	a N by J binary matrix, where the i,j-th element is the response of item j for individual i
leaf_data	a K by J matrix of logit(theta_{kj})
prior_class_probability	a length K vector, where the k-th element is the probability of assigning an individual to class k. It does not have to sum up to 1
prior_dirichlet	a vector of length K. The Dirichlet prior of class probabilities
ClassItem	a K by J matrix, where the k,j-th element counts the number of individuals that belong to class k have a positive response to item j
Class_count	a length K vector, where the k-th element counts the number of individuals belonging to class k

Value

a numeric of loglikelihood

See Also

Other likelihood functions: logllk_ddt(), logllk_ddt_lcm(), logllk_div_time_one(), logllk_div_time_two(), logllk_location(), logllk_tree_topology()

ddtlcm documentation built on May 29, 2024, 5:41 a.m.