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Computational issues with fitting joint location/dispersion models in unreplicated 2k factorials

Maximum likelihood estimation for a joint location/dispersion model has been found occasionally to experience convergence problems when applied to experiments of the 2k factorial series. We explore these problems and identify models for which the likelihood diverges or is multimodal. We derive the conditions under which this occurs and provide simple ways to check for problems both before and during computation.
Year of publication:
2011
Authors: Loughin, Thomas M. ; Rodríguez, Jorge E.
Published in:
Computational Statistics & Data Analysis. - Elsevier, ISSN 0167-9473. - Vol. 55.2011, 1, p. 491-497
Publisher: Elsevier
Keywords: Maximum likelihood Likelihood ridges Infinite likelihood Convergence problems Hessian
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Type of publication: Article
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Persistent link: https://www.econbiz.de/10008864228
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