The Rise of Markov Chain Monte Carlo Estimation for Psychometric Modeling
Author
Source
Journal of Probability and Statistics
Issue
Vol. 2009, Issue 2009 (31 Dec. 2009), pp.1-18, 18 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2009-12-30
Country of Publication
Egypt
No. of Pages
18
Main Subjects
Abstract EN
Markov chain Monte Carlo (MCMC) estimation strategies represent a powerful approach to estimation in psychometric models.
Popular MCMC samplers and their alignment with Bayesian approaches to modeling are discussed.
Key historical and current developments of MCMC are surveyed, emphasizing how MCMC allows the researcher to overcome the limitations of other estimation paradigms, facilitates the estimation of models that might otherwise be intractable, and frees the researcher from certain possible misconceptions about the models.
American Psychological Association (APA)
Levy, Roy. 2009. The Rise of Markov Chain Monte Carlo Estimation for Psychometric Modeling. Journal of Probability and Statistics،Vol. 2009, no. 2009, pp.1-18.
https://search.emarefa.net/detail/BIM-479584
Modern Language Association (MLA)
Levy, Roy. The Rise of Markov Chain Monte Carlo Estimation for Psychometric Modeling. Journal of Probability and Statistics No. 2009 (2009), pp.1-18.
https://search.emarefa.net/detail/BIM-479584
American Medical Association (AMA)
Levy, Roy. The Rise of Markov Chain Monte Carlo Estimation for Psychometric Modeling. Journal of Probability and Statistics. 2009. Vol. 2009, no. 2009, pp.1-18.
https://search.emarefa.net/detail/BIM-479584
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-479584