Box‐Cox transformations in linear models: Large sample theory and tests of normality

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Maximum likelihood estimation in semiparametric regression models with censored data (2007, methodology): “Dabrowska and Doksum (1988), Cheng et al. (1995) and Chen et al. (2002) proposed general estimators for this class of models, none of which are asymptotically efficient.”
The Box–Cox Transformation: Review and Extensions (2021, background): “In the same discussion Reid (2002) comments “The Box-Cox model is very useful for the theory of statistics, as a moderately anomalous model in the sense that blind application of conventional theory leads to absurd results.””