BISC: BISC Seminar, October 25/2001

From: masoud nikravesh (nikraves@eecs.berkeley.edu)
Date: Thu Oct 18 2001 - 11:29:39 MET DST

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    Berkeley Initiative in Soft Computing (BISC)
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    A new finite-memory algorithm for estimating the variance of the sample
    mean

                                               BISC Seminar

                                             Wheyming Song
                                              BISC Program
                                             EECS-CS Division
                                               UC Berkeley

                                           Thursday, 10/25/2001
                                              373 Soda Hall
                                               4:00:5:00pm

    Abstract:

    Estimating the variance of the sample mean is a classical problem of
    stochastic simulation. Traditional batch mean
    estimators require that the storage space in random access memory or
    disk space is proportional to the sample
    size. In this talk, we propose dynamic partial-overlapping batch mean
    estimators requiring the O(1) storage. We
    show that for no additional memory, one gets the statistical benefit of
    the 75% overlap estimators rather than
    dynamic non- overlapping batch mean estimators.

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