Multinomial models with linear inequality constraints: Overview and improvements of computational methods for Bayesian inference


Heck, Daniel W. ; Davis-Stober, Clintin P.


DOI: https://doi.org/10.1016/j.jmp.2019.03.004
URL: https://www.sciencedirect.com/science/article/abs/...
Additional URL: https://www.researchgate.net/publication/327142485...
Document Type: Article
Year of publication: 2019
The title of a journal, publication series: Journal of Mathematical Psychology
Volume: 91
Page range: 70-87
Place of publication: Amsterdam [u.a.]
Publishing house: Elsevier
ISSN: 0022-2496
Related URLs: https://arxiv.org/abs/1808.07140
Publication language: English
Institution: School of Social Sciences > Kognitive Psychologie u. Differentielle Psychologie (Erdfelder)
Subject: 150 Psychology

Dieser Eintrag ist Teil der Universitätsbibliographie.




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Heck, Daniel W. ORCID: 0000-0002-6302-9252 ; Davis-Stober, Clintin P. (2019) Multinomial models with linear inequality constraints: Overview and improvements of computational methods for Bayesian inference. Journal of Mathematical Psychology Amsterdam [u.a.] 91 70-87 [Article]


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