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Parameters for latent class profile analysis (LCPA) are easily estimated by maximum likelihood via the EM algorithm or Bayesian method via Markov chain Monte Carlo. However, the local maximum problem is a long-standing issue in any hill-climbing optimization technique for the LCPA model. To deal with multiple local modalities, two probabilistic optimization techniques using the deterministic annealing...
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