Abstract
In this article, we develop influence diagnostic tools for the tobit model. Specifically, we discuss global influence methods based on the Cook distance and residuals with envelopes, and total and conformal local influence techniques. In order to analyze the sensitivity of the maximum likelihood estimators of the parameters of the model to small perturbations on the assumptions of the model and/or data, we consider several perturbation schemes, such as case-weight and response perturbations. Finally, we illustrate the developed methodology by means of a real data set.
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Barros, M., Galea, M., González, M. et al. Influence diagnostics in the tobit censored response model. Stat Methods Appl 19, 379–397 (2010). https://doi.org/10.1007/s10260-010-0135-y
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DOI: https://doi.org/10.1007/s10260-010-0135-y