Say I run 100 entirely different estimation procedures on 100 different datasets and estimate 95% confidence intervals for each (e.g. logistic regression, linear regression, etc.). Purely based on the definition of a confidence interval, it seems like we'd expect ~95 of the intervals to capture the true parameter.

However, this is subtly different than the typical definition I've seen where confidence interval frequency properties are specific to an estimation procedure / parametric form.

Is there a good formal argument for and/or empirical example of why this cross-estimation procedure, cross-distribution frequency property holds?


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.