Statistics Colloquium: Eitan Greenshtein

Wednesday 18 March 2020, 1:30pm to 2:30pm


PSC - PSC A54 - View Map

Open to

Postgraduates, Staff


Registration not required - just turn up

Event Details

Applications of Generalized Maximum Likelihood Estimators to stratified sampling and post-stratification with many unobserved strata

Consider the problem of estimating a weighted average of the means of n strata, based on a random sample with realized Ki observations from stratum i; i = 1,..,n. This task is non-trivial in cases where for a significant portion of the strata the corresponding Ki = 0. Such a situation may happen in post-stratification, when it is desired to have very fine stratification. A fine stratification could be desired in order that assumptions, or, approximations, like Missing At Random conditional on strata, will be appealing. A fine stratification could also be desired in observational studies, when it is desired to estimate average treatment effect, by averaging the effects in small and homogeneous strata. Our approach is based on applying Generalized Maximum LikelihoodEstimators (GMLE), and ideas that are related to Non-Parametric Empirical Bayes, in order to estimate the means of strata i with corresponding Ki = 0. There are no assumptions about a relation between the means of the unobserved strata (i.e., with Ki = 0) and those of the observed strata. The performance of our approach is demonstrated both in simulations and on a real data set. Some consistency and asymptotic results are also provided.

If you want to speak with Eitan either before or after the talk please email

Contact Details

Name Dr Alex Gibberd

Telephone number

+44 1524 595068