tse_control: Estimation settings for tseLCA models

In tseLCA: Three-Step Estimation for Latent Class Analysis

Estimation settings for tseLCA models

Description

Collects the numerical settings of the three estimation steps. Pass the result as the control argument of the model-fitting functions.

Usage

tse_control(
  step1.maxit = 5000L,
  step1.tol = 1e-08,
  step1.restarts = 10L,
  step1.restart.R2 = 0.7,
  n_init = NULL,
  step3.maxit = 200L,
  step3.tol = 1e-06,
  boundary.tol = 0.01,
  hessian = c("observed", "opg"),
  verbose = FALSE
)

Arguments

step1.maxit	Maximum number of EM iterations for the Step-1 measurement model. A fit that reaches it is retried with twice as many.
step1.tol	Convergence tolerance of the Step-1 EM algorithm (change in log-likelihood).
step1.restarts	Number of additional random starts tried when the default Step-1 fit has an entropy R^2 below step1.restart.R2; the fit with the highest log-likelihood is kept.
step1.restart.R2	Entropy R^2 threshold that triggers step1.restarts.
n_init	Optional number of Step-1 fits from independent random classifications, bypassing the default k-means initialization; the fit with the highest log-likelihood is kept. Unlike step1.restarts, these always run. NULL (default) uses the default initialization.
step3.maxit	Maximum number of iterations for the Step-3 (structural model) EM or Newton-Raphson algorithm.
step3.tol	Convergence tolerance of the Step-3 algorithm.
boundary.tol	Step-1 probabilities within this distance of 0 or 1 are treated as fixed when computing the Step-1 variance.
hessian	Step-3 information matrix used for standard errors. "observed" (default) uses the analytic Hessian, giving a sandwich variance that is robust to misspecification of the Step-3 model. "opg" uses the outer product of the case-wise scores, which relies on the information-matrix equality and is valid only when the Step-3 model is correctly specified. If the Hessian cannot be inverted, "opg" is used with a warning. Applies to ML covariate models.
verbose	Logical. Print progress and convergence messages.

Value

A list of class "tse_control".

Examples

tse_control()
tse_control(step1.maxit = 10000, n_init = 20)

tseLCA documentation built on Nov. 11, 2026, 9:07 a.m.