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Re: Curve crossing point algorithm -- Bahram HOUCHMANDZADEH
New book about Exponential distribution -- isexiem@leonis.nus.sg (Xie Min)
Statistical Methods in Archaelogy -- vicovoc@chocmfg.po.my
iteratively reweighted least squares -- eek@eng.cam.ac.uk (E.E. Kuruoglu)
Re: Scrabble game -- wpilib+@pitt.edu (Richard F Ulrich)
Predictability of Sequence -- Jim Clark
Ranking and error model -- bhat@news.cs.columbia.edu (Dinkar N Bhat)
HELP with exponential smoothing, PLEASE! -- arosa@mail.telepac.pt (Antonio Rosa)
Re: Curve crossing point algorithm -- Robert Smith
Re: Scrabble game -- "Bob Wheeler"
Re: Do random events really exist? -- Dan Bonnick
butterworth bandpass -- "Harry Sommer"

Articles

Re: Curve crossing point algorithm
Bahram HOUCHMANDZADEH
Tue, 24 Jun 1997 08:24:50 +0200
Mike Brewer wrote:
> 
> I have two (for the sake of argument) *closed* loops defined by a set of
> points for each loop. What I want to do is to form the union of the two
> regions enclosed by the two loops, such that if the loops do not cross at
> all, then the union will just be the two loops. If however they DO cross,
> then I want a single loop enclosing the union.
> 
> Is the best way to go about it to find the crossing points of the two loops
> and to cut out the bits of the loop in between? If so, what is the best way
> of doing this? If not, what method should I use?
Here one not very satisfactory method :
Suppose you have two loops S1 (A,B,C,D) and S2(P,Q,R,S) :
	S1		S2
    A        B          P        Q
     D   C                S          R
To know if P belongs to the interior of S1, you have to check that P is 
always at the right side of AB,BC, CD and DA. doing that simultaneously
for all points of S2 gives you the points of S2 which belongs to the
interior of
S1. This method is fast, but assumes that some points of the
intersection
belong two both loops. All situations are not covered.
S2
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New book about Exponential distribution
isexiem@leonis.nus.sg (Xie Min)
25 Jun 1997 03:53:07 GMT
Please e-mail basu@ultrad.stat.missouri.edu for further information.
~~~~~~~~~~~~~~~~~~~~~~~~~****~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The Exponential Distribution Theory, Methods and Applications
~~~~~~~~~~~~~~~~~~~~~~~~~****~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Edited by:
N. Balakrishnan
Department of Mathematics and Statistics
McMaster University, Ontario, Canada
Asit P. Basu
Department of Statistics, University of Missouri-Columbia,
USA
Provides a systematic comprehensive treatment of the diverse literature on
the theory and applications of the exponential distribution. A
consolidation of the latest significant developments in the field, topics
covered are of the right balance and in logical sequence.  Includes
discussions on exponential regression, models and applications of mixture,
which cover the especially relevant bootstrapping method, and applications
to survival analysis.
Will be indispensable to theoretical and applied researchers in statistics,
reliability and life-testing, as well as those involved in biological,
medical, and behavioral research.
SELECTED CONTENTS
Basic Distributional Results and Properties ; Order Statistics and their
Properties ; MLEs Under Censoring and Truncation and Inference ; Linear
Estimation Under Censoring and Inference ; Reliability Estimation and
Applications ; Inferences Under Two-Sample and Multi-Sample Situations ;
Tolerance Limits and Acceptance Sampling Plans ; Prediction Problems ;
Conditional Inference and Applications ; Goodness-of-Fit tests ; Outliers
and Some Related Inferential Issues ; Extensions to Estimation Under
Multiple-Outlier Models ; Mixtures-Models and Applications ; Inference for
Multivariate Exponential Distributions ; Accelerated Life Testing with
Applications ; Systems Reliability and Associated Inference ; Exponential
Regression with Application ; Two-Stage and Multi-Stage Estimation ;
Sequential Inference ; Competing Risks Theory and Identifiability Problems
; Applications in Survival Analysis ; Applications in Queuing Theory ;
Computer Simulations
CONTRIBUTORS
M. Ahsanullah; B.C. Arnold; G.K. Bhattacharyya; R. Chappell; A. Childs;
A.C. Cohen; N. Ebrahimi; M. Engerlhardt; U. Gather; J.K. Ghosh; A.J. Gross;
J.E. Hewett; J.S. Huang; N.L. Johnson; R.A. Johnson; J.P. Klein; S. Kotz;
G.J. McLachlan; N. Mukhopadhyay; H.N. Nagaraja; S. Panchapakesan; R.A.
Sandhu; P.K. Sen; A. SenGupta; J.G. Shanthikumar; S.S. Shapiro; B.K. Sinha;
P.R. Tadikamalla; R. Viveros; L. Yeh; S. Zacks; Q. Zhang
1996- 638 + xxvi pages
Cloth ISBN 2-88449-192-9 US$119/Pound 72/ ECU92
Gordon and Breach
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Statistical Methods in Archaelogy
vicovoc@chocmfg.po.my
Tue, 24 Jun 1997 14:00:58 GMT
I am now doing a thesis on how to apply statistical methods
in archaelogy and would appreciate any information on articles
or books that i can refer to on the above subject.
Thank u very much in advance
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iteratively reweighted least squares
eek@eng.cam.ac.uk (E.E. Kuruoglu)
25 Jun 1997 11:49:08 GMT
Hello,
I am looking for fast versions of iteratively reweighted
least squares algorithm which do not require the evaluation 
of the inverse at every iteration.
Any pointers to published/unpublished work will be
very much appreciated.
Thank you,
Ercan Kuruoglu
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Re: Scrabble game
wpilib+@pitt.edu (Richard F Ulrich)
25 Jun 1997 14:38:22 GMT
Carolyn Longworth (clongwor@ultranet.com) wrote:
: Hi,
: This is probably not the place to ask this question, but I am
: desperate.  (I want to prevent a riot at the Senior Center).
: A group of Scrabble players had their year-end fete.  They determined
: the winners by taking the total of each person's game scores for the
: year and dividing this by the number of games the person played.  Some
: people only showed up for 13 games and so their total was divided by 13,
: while others showed up for all 34 games and their total was divided by
: 34.  The people who showed up for all the games claim that this method
: of determining the average scores for the year is more advantagious for
: people who play the fewest games.  Is there any truth to this?
: Thanks!
 -- As others have pointed out, it is easier to be extreme with a 
shorter series.
 -- Nobody has mentioned that the quality of competition has an 
effect on scores, so that who-plays-whom  could make a difference:
some opponents are tough; some players play defensively and make
it hard to score high (so, winning-margin might be a reasonable
criterion, rather than highest score...).  I was going to suggest
that some players might take it easy, with an easy victory in sight,
and not run up the highest score they could, but that never happened
in any Scrabble game that I lost.
If you were trying to set up a formal ranking, you might start with
the averages, and then look at narrower competition which features
only the top-scoring people.  But if you are trying to make people 
feel good, why not announce the BEST SCORE of the year, and also
HIGHEST-FIVE-SCORE-AVERAGE ?  etcetera.
Rich Ulrich, wpilib+@pitt.edu
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Predictability of Sequence
Jim Clark
Tue, 24 Jun 1997 11:13:38 -0500
Hi
Are there standard general measures of the predictability of a
sequence?  For example, could one index the overall
predictability of the numbers in a long series of the numbers
from 1 to 4, such that some series would be more predictable than
other series or some transitions in the series would be more
predictable than other transitions?  This is related to
psychological work on reaction time that I and a graduate student
are involved in, and I have _absolutely_ no mathematical
background in this area. 
Best wishes
Jim
============================================================================
James M. Clark				(204) 786-9313
Department of Psychology		(204) 774-4134 Fax
University of Winnipeg			4L02A
Winnipeg, Manitoba  R3B 2E9		clark@uwinnipeg.ca
CANADA					http://www.uwinnipeg.ca/~clark
============================================================================
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Ranking and error model
bhat@news.cs.columbia.edu (Dinkar N Bhat)
25 Jun 1997 11:24:48 -0400
Hi,
Let X_i, i=1 through n be a sample, and pi be the corresponding 
ranking obtained by sorting the data in some order. Is there
any work on relationship between the probability distribution for X
and pi? For instance, if X is from a Gaussian distribution then
what is the distribution for pi? Or if additive Gaussian noise is
added to X then how does pi get perturbed?
Any info and pointers to literature is appreciated
Dinkar
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HELP with exponential smoothing, PLEASE!
arosa@mail.telepac.pt (Antonio Rosa)
Wed, 25 Jun 1997 15:30:30 GMT
        Hi !, i'm using an programm called STATISTICA to forecast
telephones demand per month. I've acheived good results using an
linear trend in exponential smoothing, but now i'm trying to develop
an program to make the same calculations.....but i'm getting different
results. Can you help me? here are the results from the program
STATISTICA:
month: JANUARY
S0 (estimated from data) = 341884
T0 (estimated from data) = 102675
alpha=0.55 ; beta=0.1  (constants)
case   Real Values    Smoothed Series    Resids
1        393221            444559                   -51337.5
2        562774            614586                    2380.3
3        611754            682960                   -71206.1
4        803921            736751                   67169.7
5                                870344 (* forecasted) 
I'm using the following formulas:
T0=(Xn-X1)/(N-1) , where N is the length of series
S0=X1-(T0/2)
Formula of trend:   T(t)=beta* ( F(t) - F(t-1)  ) + (1-beta)*T(t-1)  ,
where T is trend and  F is forecast
F(t+1)=alpha*( A(t) ) + (1-alpha)*( F(t-1) - T(t-1) )  , where A is
the real value
 I think that this last formula is wrong, can anyone tell me the
correct formula(s) so that i can get the same values of STATISTICA ?
					Thanks in Advance!
					Antonio Rosa
----
Antonio Rosa
Portugal Telecom
Special Systems and Services
Coimbra - Portugal
mail:  arosa@mail.telepac.pt
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Re: Curve crossing point algorithm
Robert Smith
Wed, 25 Jun 1997 22:11:10 GMT
Mike Brewer wrote:
> 
> I have two (for the sake of argument) *closed* loops defined by a set of
> points for each loop. What I want to do is to form the union of the two
> regions enclosed by the two loops, such that if the loops do not cross at
> all, then the union will just be the two loops. If however they DO cross,
> then I want a single loop enclosing the union.
> 
> Is the best way to go about it to find the crossing points of the two loops
> and to cut out the bits of the loop in between? If so, what is the best way
> of doing this? If not, what method should I use?
> 
> 
> 
> Mike:   These problems are fun, but they're never as easy as they seem!  I 
would use an "edge-walker" technique, somewhat like the following.
1. Repeatedly move horizontally from one edge of the picture until you 
intersect a curve.
2. start moving along the curve in a clockwise direction.
3. When you get to some sort of a node in the curve, take the most 
COUNTERclockwise path.
4. When you return to the starting point, you will have traversed the 
periphery of the union of any intersecting curves.
5. Continue as in 1. to see if you encounter any curves you haven't 
traversed before.  The secret of this is to use a curve which is marked 
by one bit of, say, and 8-bit pixel.  You can now set various other bits 
to indicate the starting point, pixels you have already traversed, etc 
etc.  
  The main trouble you may encounter is odd-ball cases where the curves 
overlap for awhile, for example.  Also remember that unless you make 
some assumptions about shape, you can never know if the crossing of two 
lines is really two straight lines crossing or two jagged lines touching 
at one point which is also an elbow.  Also do you allow 
self-intersecting curves like a figure 8?
Have fun.
Bob
-- 
             .  Robert A. Smith, Ph.D.
  _____    .    Vision Systems' Analyst
 |     |<.      Current Technology, Inc.
 |_____|   .    (603) 868-2270
     ^       .  mailto:ras@curtech.com
    / \
   /   \
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Re: Scrabble game
"Bob Wheeler"
Wed, 25 Jun 1997 20:08:42 GMT
My reading of this was that the problem was only partially
statistical, as most real problems are. I suspect the "regular" 
players object to an "occasional" player who by chance obtains 
a very high score and thus wins a top spot. In such a case, dividing
by the range helps.  Of course, without talking to Carolyn Longwoth,
the original poster, I cannot be sure. My experience, however,
is that taking a questioner's statement about a problem at
face value often leads to a lot of work in solving the wrong
problem -- although it sometimes leads to a publication.
-- 
Bob Wheeler, ECHIP, Inc. 
    Reply to bwheeler@echip.com)
Richard F Ulrich  wrote in article
<5oragu$k0l@usenet.srv.cis.pitt.edu>...
> Carolyn Longworth (clongwor@ultranet.com) wrote:
> : Hi,
> : This is probably not the place to ask this question, but I am
> : desperate.  (I want to prevent a riot at the Senior Center).
> : A group of Scrabble players had their year-end fete.  They determined
> : the winners by taking the total of each person's game scores for the
> : year and dividing this by the number of games the person played.  Some
> : people only showed up for 13 games and so their total was divided by
13,
> : while others showed up for all 34 games and their total was divided by
> : 34.  The people who showed up for all the games claim that this method
> : of determining the average scores for the year is more advantagious for
> : people who play the fewest games.  Is there any truth to this?
> : Thanks!
> 
>  -- As others have pointed out, it is easier to be extreme with a 
> shorter series.
> 
>  -- Nobody has mentioned that the quality of competition has an 
> effect on scores, so that who-plays-whom  could make a difference:
> some opponents are tough; some players play defensively and make
> it hard to score high (so, winning-margin might be a reasonable
> criterion, rather than highest score...).  I was going to suggest
> that some players might take it easy, with an easy victory in sight,
> and not run up the highest score they could, but that never happened
> in any Scrabble game that I lost.
> 
> If you were trying to set up a formal ranking, you might start with
> the averages, and then look at narrower competition which features
> only the top-scoring people.  But if you are trying to make people 
> feel good, why not announce the BEST SCORE of the year, and also
> HIGHEST-FIVE-SCORE-AVERAGE ?  etcetera.
> 
> 
> Rich Ulrich, wpilib+@pitt.edu
> 
> 
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Re: Do random events really exist?
Dan Bonnick
Mon, 23 Jun 1997 23:32:18 +0100
In article <33AA08EB.75F61B58@eos.ncsu.edu>, "Pavel E. Guarisma"
 writes
>ModTollens wrote:
>> 
>> Such an interesting thought.  I think this allows me to ask the question,
>> "Is life fair?"
>> I am very interested in any response.
>
>Sure!
>Life, in the long run, is fair!!
[apologies in advance for the near-crosspost]
What about the second law of thermodynamics?
>
>The central limit theorem allows us to assume a normal distribution for
>large number of observations of any random variable. So this means that,
>in the long run, the bad stuff that happens should even out with the
>good stuff that happens. Furthermore, since bad experiences and good
>experiences should cancel each other out in the long run then the mean
>of this Gaussian should be zero.
I don't know about you, but I think my life is finite - there won't be
enough time to get to the central limit...
Dan Bonnick
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butterworth bandpass
"Harry Sommer"
26 Jun 1997 07:05:28 GMT
Hi,
in an image processing book I read of a butterworth radially symmetric
bandpass filter and this is exactly what I need for my filter problem.
Unfortunately I do not know how the formula of such butterworth bandpass
filter looks like. So it would be very helpful if someone can give me the
formula.
Thanks
Harry
Harry Sommer
Lehrstuhl fuer Landschaftsoekologie
TU Muenchen-Weihenstephan
harry@pollux.edv.agrar.tu-muenchen.de
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