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  <title>sci.stat.math Google Group</title>
  <link>http://groups.google.com.au/group/sci.stat.math</link>
  <description>Statistics from a strictly mathematical viewpoint.</description>
  <language>en</language>
  <item>
  <title>Re: Mechanical generation of random bit sequences</title>
  <link>http://groups.google.com.au/group/sci.stat.math/browse_thread/thread/a2baf2d6f29cc216/ccff0397068f948d?show_docid=ccff0397068f948d</link>
  <description>
  If I understand you correctly, you favour collecting randomness &lt;br&gt; through user&#39;s typing on keyboard or mouse movements. I don&#39;t know &lt;br&gt; what&#39;s exactly with mouse movements, but in the case of keystrokes &lt;br&gt; I guess that the randomness might be questionable. My thinking on &lt;br&gt; this comes from the fact that typing on keyboard could be employed
  </description>
  <guid isPermaLink="true">http://groups.google.com.au/group/sci.stat.math/browse_thread/thread/a2baf2d6f29cc216/ccff0397068f948d?show_docid=ccff0397068f948d</guid>
  <author>
  mok-kong.s...@t-online.de
  (Mok-Kong Shen)
  </author>
  <pubDate>Sat, 21 Nov 2009 19:09:26 UT
</pubDate>
  </item>
  <item>
  <title>Re: Mechanical generation of random bit sequences</title>
  <link>http://groups.google.com.au/group/sci.stat.math/browse_thread/thread/a2baf2d6f29cc216/702f8488df10298a?show_docid=702f8488df10298a</link>
  <description>
  Do you know why it tends not to get used? &lt;br&gt; Thanks, &lt;br&gt; M. K. Shen
  </description>
  <guid isPermaLink="true">http://groups.google.com.au/group/sci.stat.math/browse_thread/thread/a2baf2d6f29cc216/702f8488df10298a?show_docid=702f8488df10298a</guid>
  <author>
  mok-kong.s...@t-online.de
  (Mok-Kong Shen)
  </author>
  <pubDate>Sat, 21 Nov 2009 19:09:32 UT
</pubDate>
  </item>
  <item>
  <title>Adjusted regression beta</title>
  <link>http://groups.google.com.au/group/sci.stat.math/browse_thread/thread/59bc29586b1ef023/d1744ca3ddf2a33c?show_docid=d1744ca3ddf2a33c</link>
  <description>
  There is a paper by Dimson(1979) that calls for adjusted beta when you have thin trading: &lt;br&gt; without thin trading the regression is: &lt;br&gt; Stock return= intercept + beta*( market Index return) &lt;br&gt; i.e r=a +b (rm) &lt;br&gt; with the adjustment the model becomes: &lt;br&gt; r=a+(one period lag beta)*(one period lag market return) +(contemporaneous beta)*(contemporaneous market return) + (one period lead beta)*(one period lead market return)
  </description>
  <guid isPermaLink="true">http://groups.google.com.au/group/sci.stat.math/browse_thread/thread/59bc29586b1ef023/d1744ca3ddf2a33c?show_docid=d1744ca3ddf2a33c</guid>
  <author>
  danielleblanc2...@hotmail.com
  (Daniel)
  </author>
  <pubDate>Sat, 21 Nov 2009 19:07:15 UT
</pubDate>
  </item>
  <item>
  <title>Re: KPSS Test for time series forecasting for using ARIMA</title>
  <link>http://groups.google.com.au/group/sci.stat.math/browse_thread/thread/6ce2cade90e9276d/8d756773e1200618?show_docid=8d756773e1200618</link>
  <description>
  I forgot more artificial circumstance. Even after you have a good &lt;br&gt; estimate of B1 = 1, your software may or may not be able to estimate &lt;br&gt; {Et}. I suspect that it is not commonly known how to do so.
  </description>
  <guid isPermaLink="true">http://groups.google.com.au/group/sci.stat.math/browse_thread/thread/6ce2cade90e9276d/8d756773e1200618?show_docid=8d756773e1200618</guid>
  <author>
  aruzin...@general-cathexis.com
  (aruzinsky)
  </author>
  <pubDate>Sat, 21 Nov 2009 17:09:03 UT
</pubDate>
  </item>
  <item>
  <title>Re: KPSS Test for time series forecasting for using ARIMA</title>
  <link>http://groups.google.com.au/group/sci.stat.math/browse_thread/thread/6ce2cade90e9276d/4df3514c1a210665?show_docid=4df3514c1a210665</link>
  <description>
  &amp;quot;why do we even have to fit against a trend line?&amp;quot; &lt;br&gt; If you difference Yt = A*t + B + Et, where {Et} is white, zero mean, &lt;br&gt; you get (Yt - Yt-1 - A) = Et - Et-1 which is an MA process with a zero &lt;br&gt; on the unit circle. If you difference a random walk, Xt = Xt-1 + Et, &lt;br&gt; you have no such MA process. Depending on the algorithm, your
  </description>
  <guid isPermaLink="true">http://groups.google.com.au/group/sci.stat.math/browse_thread/thread/6ce2cade90e9276d/4df3514c1a210665?show_docid=4df3514c1a210665</guid>
  <author>
  aruzin...@general-cathexis.com
  (aruzinsky)
  </author>
  <pubDate>Sat, 21 Nov 2009 16:55:46 UT
</pubDate>
  </item>
  <item>
  <title>Re: Mechanical generation of random bit sequences</title>
  <link>http://groups.google.com.au/group/sci.stat.math/browse_thread/thread/a2baf2d6f29cc216/979570a84c965b2f?show_docid=979570a84c965b2f</link>
  <description>
  REcent ( last 5 years or so) Intel cpus already have a hardware random &lt;br&gt; number generator on the cpu AFAIK. It tends not to get used.
  </description>
  <guid isPermaLink="true">http://groups.google.com.au/group/sci.stat.math/browse_thread/thread/a2baf2d6f29cc216/979570a84c965b2f?show_docid=979570a84c965b2f</guid>
  <author>
  unruh-s...@physics.ubc.ca
  (Unruh)
  </author>
  <pubDate>Fri, 20 Nov 2009 21:53:03 UT
</pubDate>
  </item>
  <item>
  <title>Re: regression question</title>
  <link>http://groups.google.com.au/group/sci.stat.math/browse_thread/thread/b45465ef51d74708/eba08bf586e73e36?show_docid=eba08bf586e73e36</link>
  <description>
  That&#39;s an interesting point, Ray, and I think you are correct. &lt;br&gt; BTW, all of the independent variables (X1...X5) are valid for the time &lt;br&gt; of landfall. &lt;br&gt; Sometimes, as a hurricane grows larger in size (e.g., the wind field &lt;br&gt; becomes larger), its intensity decreases, and vice versa. Ergo, the &lt;br&gt; behavior of the X1 (size) and X2 (intensity) components often sends
  </description>
  <guid isPermaLink="true">http://groups.google.com.au/group/sci.stat.math/browse_thread/thread/b45465ef51d74708/eba08bf586e73e36?show_docid=eba08bf586e73e36</guid>
  <author>
  icyst...@hotmail.com
  (icystorm)
  </author>
  <pubDate>Fri, 20 Nov 2009 20:26:39 UT
</pubDate>
  </item>
  <item>
  <title>Re: regression question</title>
  <link>http://groups.google.com.au/group/sci.stat.math/browse_thread/thread/b45465ef51d74708/da89a70334038600?show_docid=da89a70334038600</link>
  <description>
  Any method that ignores the landfall is doomed to failure. This &lt;br&gt; reminds me of a WWII story about Allied attempts to construct a &lt;br&gt; regression equation for the size of bombing errors. They discovered &lt;br&gt; that the number of interceptors the bombers encountered got a negative &lt;br&gt; weight, with more interceptors leading to smaller errors. Until they
  </description>
  <guid isPermaLink="true">http://groups.google.com.au/group/sci.stat.math/browse_thread/thread/b45465ef51d74708/da89a70334038600?show_docid=da89a70334038600</guid>
  <author>
  koop...@sfu.ca
  (Ray Koopman)
  </author>
  <pubDate>Fri, 20 Nov 2009 19:36:19 UT
</pubDate>
  </item>
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  <author>
  ecyaya...@yeah.net
  (hero)
  </author>
  <pubDate>Fri, 20 Nov 2009 19:12:00 UT
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  </item>
  <item>
  <title>Re: Mechanical generation of random bit sequences</title>
  <link>http://groups.google.com.au/group/sci.stat.math/browse_thread/thread/a2baf2d6f29cc216/b205cd720a1e8690?show_docid=b205cd720a1e8690</link>
  <description>
  There are not many ways I can imagine someone doing technically incorrectly: &lt;br&gt; * Holding a key instead of hitting many keys. The key repeat events &lt;br&gt; should be easily detected and ignored by the software. &lt;br&gt; * Not hitting any keys or not moving the mouse at all. &lt;br&gt; Software can be communicate the error to the user and any user who would
  </description>
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  <author>
  bernh...@bksys.at
  (Bernhard Kuemel)
  </author>
  <pubDate>Fri, 20 Nov 2009 18:12:51 UT
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  </item>
  <item>
  <title>Re: regression question</title>
  <link>http://groups.google.com.au/group/sci.stat.math/browse_thread/thread/b45465ef51d74708/5994fb53dff54635?show_docid=5994fb53dff54635</link>
  <description>
  Joseph, &lt;br&gt; I took a look at this problem using a branch and bound algorithm &lt;br&gt; recommended in a recent article (&amp;quot;An Exact Algorithm for &lt;br&gt; Heirarchically Well-Formulated Subsets in Second-Order Polynomial &lt;br&gt; Regression&amp;quot;, Technometrics, Vol. 51 No. 3, August 2009). &lt;br&gt; I used the sqrt(y) as the response as has been previously recommended.
  </description>
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  <author>
  david.schw...@goodstats.biz
  (GoodStats)
  </author>
  <pubDate>Fri, 20 Nov 2009 15:25:42 UT
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