Abstract
The paper discusses a likelihood based method of estimation which allows for a small amount of misspecification in the assumption of normality. Asymptotic results suggest that the new method can give an estimated model which is closer to the true model. An application to hearing threshold data is discussed.
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Copas, J., Stride, C. Fitting a Normal Distribution When the Model is Wrong. Annals of the Institute of Statistical Mathematics 49, 601–614 (1997). https://doi.org/10.1023/A:1003220407410
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DOI: https://doi.org/10.1023/A:1003220407410