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Model robust confidence intervals using maximum likelihood estimators. (English) Zbl 0596.62032

Summary: Standard large-sample confidence intervals about a maximum likelihood estimator \({\hat \theta}\) are two-thirds robust; i.e. when the parametric model is imperfect \({\hat \theta}\) often remains consistent and asymptotically normal. The confidence intervals are invalidated only because the third necessary condition, consistency of the variance estimator, fails. The ’delta method’ provides a simple alternative variance estimator which remains consistent under more general conditions and provides robust large-sample confidence intervals.

MSC:

62F35 Robustness and adaptive procedures (parametric inference)
62F25 Parametric tolerance and confidence regions
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