[Ml-stat-talks] Fwd: [ORFE-Seminars] Wilks Statistics Seminar: Eitan Greenshtein, Friday, Mar. 10, 2017 12:30 PM, Sherrerd Hall 101
bee at princeton.edu
Fri Mar 3 14:57:42 EST 2017
Talk of interest.
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*** Wilks Statistics Seminar ***
DATE: Friday, March 10, 2017
TIME: 12:30 pm
LOCATION: Sherrerd Hall 101
SPEAKER: Eitan Greenshtein, Central Bureau of Statistics, Israel
TITLE: Non-parametric Empirical Bayes Improvement of Common Shrinkage
ABSTRACT: We consider the problem of estimating a vector (µ1,...,µn) of
normal means under a squared loss, based on independent Y_i ∼ N(µ_i,1), i =
1,...,n. We use ideas and techniques from non-parametric empirical Bayes,
to obtain asymptotical risk improvement of classical shrinkage estimators,
such as, Stein's estimator, Fay-Herriot, Kalman filter, and more. We
consider both the sequential and retrospective estimation problems. We
elaborate on state-space models and the Kalman filter estimators. The
performance of our improving method is demonstrated both through
simulations and real data examples.
Joint work with Ariel Mansura, and Ya'acov Ritov
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