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Subject:

ALLSTAT XPOST: RSS meeting, paper available

From:

Dr SA Peters <[log in to unmask]>

Reply-To:

Dr SA Peters <[log in to unmask]>

Date:

Sun, 20 Jan 2002 18:18:05 +0000

Content-Type:

text/plain

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text/plain (72 lines)

From [log in to unmask] Sun Jan 20 12:34:49 2002
Received: from probity.mcc.ac.uk (probity.mcc.ac.uk [130.88.200.94])
        by irwell.mimas.ac.uk (8.10.2+Sun/8.9.3) with ESMTP id g0KCYnT29950
        for <[log in to unmask]>; Sun, 20 Jan 2002 12:34:49 GMT
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Message-ID: <[log in to unmask]>
Date: Sun, 13 Jan 2002 11:06:04 +0000
From: Simon Peters <[log in to unmask]>
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To: [log in to unmask]
Subject: ALLSTAT XPOST: RSS meeting, paper available

Dear All,

This may of interest.
The paper is available for those unable to attend (see the link below).
Note however, that this may not be available after the meeting as the article
is to appear in RSS B.

Subject:      Royal Statistical Society Ordinary Meeting

        Royal Statistical Society Ordinary Meeting
        ------------------------------------------
          February 13, 2002, 5pm (Tea from 4.30pm)

       at the Royal Statistical Society lecture room
              12 Errol Street, London EC1Y 8LX.

An Adaptive Estimation of Dimension Reduction Space
--------------------------------------------------

    Yingcun Xia (University of Hong Kong and University of Cambridge)
    Howell Tong (University of Hong Kong and LSE)
    WK Li (University of Hong Kong) and
    Li-Xing Zhu (University of Hong Kong and Chinese Academy of Sciences)

Summary
-------
In regression, how to best approximate the regression function or view
high dimensional data in a (hopefully much) lower dimensional subspace
is of primary importance. We present an approach which makes no parametric
assumption on the functional form of the regression surface, does not
restrict the regressors to be independent or to follow any particular type
of distribution, and requires no under-smoothing of the nonparametric
estimate of the unknown regression function.

A PDF copy of the paper can be downloaded from
http://www.rss.org.uk/publications/preprints.html#130202

Contact Anna Mair (email [log in to unmask]) at the RSS for further
details and for a hard copy of the paper (stating your full address).

        Discussion at RSS ordinary meetings
        -----------------------------------
Contributions to the discussion at Ordinary Meetings are welcome, whether in
person at the meeting or subsequently in writing. However, contributions must
not exceed 5 minutes' speaking time and 400 words for publication in the
journal (excluding details of any references quoted). In either case, written
versions should be sent to the Executive Editor at the Royal Statistical
Society, 12 Errol Street, London, EC1Y 8LX, to arrive no later than 2 weeks
after the meeting. If time allows, contributions received before the day of
the meeting may be read out on behalf of anyone who cannot attend.

  ------------------------------------------------------------------------

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