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

Thomas M. Loughin and Jorge E. Rodríguez

Computational Statistics & Data Analysis, 2011, vol. 55, issue 1, 491-497

Abstract: 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.

Keywords: Maximum; likelihood; Likelihood; ridges; Infinite; likelihood; Convergence; problems; Hessian (search for similar items in EconPapers)
Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:55:y:2011:i:1:p:491-497

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