A Bayesian Approach to Nonlinear Latent Variable Models Using the Gibbs Sampler and the Metropolis-Hastings Algorithm

Nonlinear latent variable models are specified that include quadratic forms and interactions of latent regressor variable as special cases. To estimate the parameters, the models are put in a Bayesian framework with conjugate priors for the parameters. The proposed estimation methods are illustrated...

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Veröffentlicht in:	Psychometrika 1998-09, Vol.63 (3), p.271-300
Hauptverfasser:	Arminger, Gerhard, Muthen, Bengt O
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Bayesian Statistics Biological and medical sciences Estimation (Mathematics) Fundamental and applied biological sciences. Psychology Gibbs Sampling Latent Variables Mathematical Models Nonlinear Models Psychology. Psychoanalysis. Psychiatry Psychology. Psychophysiology Psychometrics. Statistics. Methodology Simulation Statistics. Mathematics
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