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

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  • Loughin, Thomas M.
  • Rodríguez, Jorge E.

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.

Suggested Citation

  • Loughin, Thomas M. & Rodríguez, Jorge E., 2011. "Computational issues with fitting joint location/dispersion models in unreplicated 2k factorials," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 491-497, January.
    • Handle: RePEc:eee:csdana:v:55:y:2011:i:1:p:491-497
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    References listed on IDEAS

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    1. Harvey, A C, 1976. "Estimating Regression Models with Multiplicative Heteroscedasticity," Econometrica, Econometric Society, vol. 44(3), pages 461-465, May.
    2. Wang, P. C., 1989. "Test for dispersion effects from orthogonal arrays," Computational Statistics & Data Analysis, Elsevier, vol. 8(1), pages 109-117, May.
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