HDTenEightyP/NetNews huggingface dataset:
From: chasman@athena.mit.edu (David Chasman)
Subject: Help ! Silly question from a novice ( Clarification )
Organization: Massachusetts Institute of Technology
Date: Thu, 19 Nov 1992 18:15:22 GMT

This is probably a silly question, but I can't learn if I don't ask
questions:

(1) I have M observations x1,x2,x3,....,xM

(2) I have N sets of unknown values U(1),U(2),...,U(N).
    We will refer to the elements of the sets as
    U(1) = { U(1,1) , U(1,2) , ..... , etc }
    U(2) = { U(2,1) , U(2,2) , ..... , etc }
    ... you get the idea.

    Remember: the U(i,j) are unknown .
    

(3) I hypothesize that each of my x(i) is the sum of
    one element chosen from U(1),U(2),.... . That is :

    x(i) = U(1,i1[i]) + U(2,i2[i]) + U(3,i3[i]) + ... + U(N,iN[i])
 
    where at least one of the i1[i],i2[i],i3[i],..,iN[i] is different for
    each of the x(i).

Questions :
(A) How can I get an estimate of the probability that this is true ?
(B) Can I compare the results I get for different N ( see (2) above ) ?
    i.e. - is there a way to determine the best value of N ?

Thankyou in advance.
--David Chasman

Newsgroups: sci.math.stat
From: sharriso@magnus.acs.ohio-state.edu (Steven K Harrison)
Subject: Canonical discriminant analysis
Organization: The Ohio State University
Distribution: usa
Date: Mon, 23 Nov 1992 13:14:30 GMT

I recently received a manuscript to review in which the authors used canonical 
discriminant analysis to look at the association of certain plant species with 
different soil types.  As a non-statistician and someone familiar only with 
more traditional multivariate techniques, I would appreciate a brief
explanation of canonical discriminant analysis (or a good reference).

Gracias.
Newsgroups: sci.math.stat
From: thng@atri.curtin.edu.au (Ian Li-Jin Thng)
Subject: Help ! Mathematica and Maple Road test
Reply-To: thng@atri.curtin.edu.au
Organization: Australian Telecommunication Research Institute
Date: Wed, 18 Nov 92 17:39:58 GMT

G'day all math netters,

Would really appreciate on any information regarding the strengths
and weaknesses of two very popular symbolic math packages - Maple
and Mathematica. I'm not too sure which to go for but as far as the
brochures are concerned , both seems to be pretty impressive. 

Basically : 

I'm looking for something which provides an extensive repertoire (sp?)
of well known functions and algos. Ie, comes with numerous math packages
for linear algebra, matrix manipulation and inversion , complex number,
non-linear as well as linear optimizations - you know - stuffs like that

Basically - I'm sick and tired of programming in Fortran with NAG . Also
running out of cash to upkeep NAG annually. Would like a math package that 
have functions equivalent or similar to NAG routines so that I can chuck 
Fortran and Nag away. I can use both UNIX and DOS based Windows 3.1 
environments.
  
Is there anyone out there whose used both and can answer my queries ?

Better still, if there is an FTp site where I can get comprehensive infos 
on these two packages , please do tell me about it too !  Here's how to 
contact me :

 

------------------------------------------------------------------------------
                 Ian Thng  - Forever Trying to be Young  
                 Email:thng@atri.curtin.edu.au
                 Adaptive Signal Processing Laboratory
                 Australian Telecommunications Research Institute
                 Curtin University of Technology
                 Ph :  +61-9-3513270
                 Fax : +61-9-3513244 
                 Bothered with seat belts ? Ride a Harley Mate !
------------------------------------------------------------------------------


A thousand thanx in advance to anyone who can help !!!



Newsgroups: sci.math.stat
From: muttiah@thistle.ecn.purdue.edu (Ranjan S Muttiah)
Subject: Method of Moments (for pde)
Organization: Purdue University Engineering Computer Network
Date: Mon, 23 Nov 1992 03:54:40 GMT


There's the diffusion eqn. in 2-D given by (all d's are partials):

	D d^2{C}/dx^2 + D d^2{C}/dy^2 + V dC/dx + V dC/dy = dC/dt

I want to use the method of moments to get at D (2^nd rank tensor) and V.
For the case of a single dimension, one could multiply by x^N (or y^N)
and then using the chain rule trick get these two.  How do I get these
two creatures in 2-D ?
Newsgroups: sci.math.stat
From: zoubeidi@masg1.epfl.ch (Toufik Zoubeidi)
Newsgroups: sci.math.stat
Subject: Quartiles in S-plus
Date: 17 Nov 92 16:00:05 GMT
Organization: Ecole Polytechnique Federale de Lausanne

Hello, 

In preparing a class example we found out that in computing quartiles
S-plus uses different methods under different commands. The method
used in the commands "summary" or "quantile" is different from the 
one used to compute quartiles for a boxplot in the command "boxplot".
We know which method is used in each case. Does anyone know the reason
for this difference.

Below is the illustration of this

>X      (The data)

  24  11 107  18  29  49  94  12  16  22 141  18  21  13  11

>summary(X)

 Min. 1st Qu. Median  Mean 3rd Qu. Max. 
   11    14.5     21 39.07      39  141

>A <- boxplot(X, plot=F)
>A

$stats:
     [,1] 
[1,]   94
[2,]   49  <-- 3rd Qu. 
[3,]   21  
[4,]   13  <-- 1st Qu.
[5,]   11

$n:
[1] 15


$out:
[1] 107 141  <-- If the quartiles computed in "summary" were used
                 then 94 will also be out. 

$group:
[1] 1 1

Bye, Toufik.

Newsgroups: sci.math.stat
From: gln@iti.org (Glen Niebur)
Subject: Statistics on the Mac
Organization: Mayo Foundation, Rochester MN. Campus
Distribution: World
Date: 19 Nov 92 19:25:22 GMT

I apologize in advance as i am sure this is a FAQ, but i don't normally read
this group.  Can someone suggest a good statistics package for the Mac?

We are looking for ANOVA, paired and multi way comparisons, T tests, repeated
measures, and things like that.  (I apologize if these terms are incorrect,
I'm asking for things that *other people* are asking me for.)

I have gotten suggestions of Statistica, and Statview.  Any reviews?  Any
other suggestions?

Thanks in advance.

Glen

--
Glen Niebur     | Living in a world we didn't make,
Mayo Clinic     | Living in a world that's filled with hate,
Biomechanics Lab| Living in a world where grownups break the rules.
gln@mayo.edu    |            ~Janet Jackson
Newsgroups: utstat.general,sci.math.stat,ont.events
From: ruth@utstat.uucp (Ruth Croxford)
Subject: Statistics Seminar - Prof. J.K. Ghosh
Organization: U of Toronto Statistics
Distribution: ont
Date: Tue, 17 Nov 1992 17:55:29 GMT
Expires: 27-ont-1992

Colloquium - Department of Statistics, University of Toronto

Topic:     Decision Rule for Dimension in the Context of Manova
Speaker:   Prof. J.K. Ghosh
	   Purdue University and Indian Statistical Institute
Date:      Thursday, November 26    4:00 - 5:00
Place:     Room 1073, Sidney Smith Hall, 100 St. George Street
Abstract:

In the context of Multivariate Analysis of Variance (MANOVA), it is 
of interest to know the dimension of the space generated by the population
mean vectors centered at zero.  This would help identification of a 
structural relation, if there is any.  Formally, we have p normal
populations each of dimension  d, p > d.  Let the mean vectors be 
mu sub 1, ..., mu sub p and omega the common disperson matrix.

Let M = (mu sub 1 - mu bar, mu sub 2 - mu bar, ..., mu sub p - mu bar) 
where mu bar = p sup -1 SIGMA sub {mu i}.  We have actions or decisions 
a sub 0, ..., a sub d, where a sub i is the decision M has rank i.

We propose an intuitively appealing ad hoc rule, then show it is close to
being Bayes for a suitable prior and finally refine the ad hoc rule in
the light of the Bayes rule.  Its performance is studied in the frequentist 
paradigm.  We also report briefly on ongoing work with Rahul Mukerjee on 
construction of reference and other non-informative priors and their use
in a Bayesian treatment of this problem.  We focus on the case of known 
OMEGA and d = 2, but indicate what is to be done for general
d and unknown OMEGA $.  (This work is joint with Anindya De).
________________________________________________________________________________
Coffee, Tea and Cookies will be served in the Delury Lounge (SS6004) at 3:30 p.m.
Newsgroups: sci.math.stat
From: katholi@willis.cis.uab.edu (C.R. Katholi)
Subject: ARIMA Code needed
Organization: University of Alabama at Birmingham
Date: Wed, 18 Nov 1992 15:23:06 GMT

     I am posting this for a friend who does not have e-mail access. Please
send all responses to me: katholi@cis.uab.edu

                       W A N T E D

Software to perform the following tasks:
    
     Box-Jenkins Time Series ARIMA Model Analysis
	- Parameter estimation
	- Autocorrelation coefficient estimation
	- Partial autocorrelation coefficient estimation

Code should output parameters in a form usable for subsequent analysis.
The desired routines should be in FORTRAN and be suitale for use on
a CRAY. Codes needed because of problems with IMSL routines on the
available CRAY. Source code desired. Code hopefully available by
anonymous ftp.

     Thank you in advance for your assistance.

						- Tonya Smoot




Newsgroups: sci.math.stat
From: roy@biostat.med.umich.edu (Roy St. Laurent)
Subject: Re: Calculating variances
Date: Fri, 20 Nov 92 10:47:07 EST
Organization: University of Michigan Biostatistics, Ann Arbor
Reply-To: roy@sol.biostat.med.umich.edu (Roy St. Laurent)
Keywords: variance
Originator: roy@sol


In article <luke.722264309@barney>, luke@cs.city.ac.uk (Luke Whitaker) writes:
|> 
|> It seems that the only general rule for computing variances is for the sum or
|> difference of random variables (ie var(x+/-y) = var(x) + var(y)). What about 
|> products, reciprocals and other arbitrary combinations of random variables. 
|> I realise that this is non-trivial and that there is no simple answer as 
|> there is for sums and differences but there must be techniques to get a 
|> handle on this.
|> 
|> Could someone point me in the right direction, references etc for this problem.

An approximate answer to your question is given by the delta-method -- a method
for finding the asymptotic variance of f(x) for some smooth function f(.), as a 
function of var(x).
   In the simplest case, the delta method gives:
         approx var(f(x)) = f'(mu)^2 var(x)   
where f'(mu) is the first derivative of f evaluated at mu=E(x).
    For ratios of random variables and other functions, a more general 
(multivariate) version of the delta method may be used.  See either of the
references below for the details.
   
Ref'ns
  Bishop,YMM, Fienberg,SE, & Holland, PW (1975).  Discrete Multivariate Analysis:
Theory and Practice.  MIT Press: Cambridge, Mass. p486-502. 
  Serfling, RJ (1980).  Approximation Theorems of Mathematical Statistics.  Wiley:
New York.

 -- Roy St. Laurent
    Biostatistics
    Univ. of Mich.
    roy@sol.biostat.med.umich.edu
-- 
  -- Roy St. Laurent (roy@biostat.med.umich.edu)

"Even $10 calculators have sigma buttons.  [I] haven't seen one with an 
 M-estimator button, yet."         --Jerry Dallal in sci.math.stat
Newsgroups: sci.math.stat
From: mfdjh@uxa.ecn.bgu.edu (Dale Hample)
Subject: mathcad for windows
Organization: Educational Computing Network
Date: Thu, 19 Nov 1992 15:29:16 GMT

I just got an offer in the mail for mathcad for $79.  I'm tempted, but:
(a) I'm not a statistician, just a user, & (b) I've learned & forgotten
calculus three times.  I realize that mathcad won't do serious
multivariate stuff for me...I've got spss for that...but I'm wondering
how useful it will be in deepening my understanding of the packaged
stats.  Are there macros or something for mathcad that illustrate
statistical procedures, etc...distributions, transformations, steps in
multivariate procedures?
-- 
Dale Hample                            Dept. Communication A&S
mfdjh@ecnuxa.bitnet                    Western Illinois University
mfdjh@uxa.ecn.bgu.edu                  309-298-1492
        The beatings will continue until morale improves.
From: peterw@zen.maths.uts.edu.au (Peter Wright)
Newsgroups: sci.math.stat
Subject: Re: sigma from range
Date: 22 Nov 92 22:45:37 GMT
Organization: University of Technology, Sydney
NNTP-Posting-Host: zen.maths.uts.edu.au

In <1992Nov20.161226.27020@nosc.mil> marchett@antares.nosc.mil (Dave Marchette) writes:

>Let x1,...,xn be iid normal 0, sigma, and let x(1),...,x(n)
>be the order statistics.  Assume that only n and x(n)-x(1)
>are known.  That is, only the number of points and the total
>spread of the points is known.  What is the appropriate estimate 
>of sigma?

An unbiased estimator of sigma is the range divided by a constant (which is
a function of n). Unfortunately there is no nice closed expression for the
constant, since it is the solution to an integral equation. However the
constant is tabulated in lots of places, especially in quality control texts.
Some refs:

Pearson E.S. (1942) "The Probability Integral of the Range ...", 
	Biometrika, 32, p.301-310.
Dixon, W.J. & Massey, F.J. (1969) "Introduction to Statistical Analysis",
	McGraw-Hill, p.136, p.486.
Duncan, A.J. (1986) "Quality Control and Industrial Statistics", Irwin,  
	p.481, p.1005.
Montgomery, D.C. (1991) "Introduction to Statistical Quality Control", Wiley,
	p.204, p.A-15.

--
===============================================================================
  PETER WRIGHT, School of Math Sc,      |  Email: peterw@zen.maths.uts.edu.au
  University of Technology, Sydney      |  Phone:      (612) 330 2243
  PO Box 123, Broadway 2007, Australia  |  Fax  :      (612) 330 2243
From: phd85@keele.ac.uk (D.H. Holden)
Newsgroups: sci.math.stat
Subject: Layman Q. : Cluster analysis?
Date: 21 Nov 92 12:31:28 GMT
Organization: Keele University, England


 Hi,
   Can any one tell me in layman terms what cluster analysis is,
   and maybe give an example of its uses.
   Thanks alot Dave.

--
                                                                     

phd85@uk.ac.keele.seq1
keele university.
From: joe@decoy.uoregon.edu (Joe St Sauver)
Newsgroups: sci.math.stat
Subject: Re: X11
Date: 20 Nov 1992 01:43:31 GMT
Organization: University of Oregon Network Services
NNTP-Posting-Host: decoy.uoregon.edu
Keywords: X11, time series, seasonality

In article <1992Nov19.112801.4975@isy.liu.se> pomat@math.liu.se (Pontus  
Matstoms) writes:
> I'm looking for references concerning the X11 method for time series  
analysis.
> What is the method used for and are there any known public domain  
implementations ?

X-11 does seasonal adjustment of monthly or quarterly data, using a 
decomposition method based on separating seasonal patterns from 
trend, cyclical, trading day and irregular fluctuations.

The canonical references for X-11 are: 

 US Bureau of the Census (1967), X-11 Variant of the Census Method II
 Seasonal Adjustment Program, US Dept of Commerce, Tech Paper 15 (1967
 revision), Washington DC: Gov't Printing Office.

 US Bureau of the Census (1969), X-11 Information for the User, US
 Dept of Commerce, Washington DC: Gov't Printing Office.

SAS/ETS offers a nice implementation of the procedure.

Regards,

Joe St Sauver (joe@oregon.uoregon.edu)
Assistant Director, Academic User Services
Newsgroups: sci.math.stat
From: iwelch@agsm.ucla.edu (Ivo Welch)
Subject: Questions on GS-Causality With Panel Data Set
Organization: UCLA, Anderson Graduate School Of Management
Date: 18 Nov 92 14:53:28 PST


I  have   a basic understanding  of Granger-Simms   causality  (or, better, GS
temporal ordering). I have seen bivariate time-series tests in two flavors:

	[1] a vector autoregression (Y_0= a Y_-1 + b X_-1 + n)
	[2] two time-series regressions and a subsequent correlation
	of the residuals (Y_0 = a Y_-1 + n_t; X_0 = b X_-1 + m_t;
	if n_t-1 correlates with m_t, then "Y sort of causes X".

I presume that the first method is less restrictive than  the first, but loses
a little by mixing expected changes with unexpected changes.  (I may be wrong,
here, altogether.) Further, multivariate extensions are a bit  less natural in
the second procedure.

Most studies seem to perform either of  these analyses with  long time series.
Yet, I  have a  panel data set   with only 5 years  of  data, but thousands of
firms/people.  My question  is whether it makes much  sense  to  run the above
regressions cross-sectionally (and year-by-year or pooled),  and claim GS-like
causality.  It does appear to be different; the  relevant statement is now how
does a cross-sectional outlier  in X_{i,t-1} correlate with a  cross-sectional
outlier in Y_{i,t}.

Are   there comparable   studies   (especially if    these    studies use easy
computational/notational  methods; I am less  interested  in asymptotic theory
than I am interested in actual use).

Thanks.

/ivo welch
Newsgroups: sci.math.stat
From: mitchllj@vax1.tcd.ie
Subject: nonlinear time series analysis
Organization: Trinity College Dublin
Date: Mon, 23 Nov 1992 15:20:19 GMT

I'm looking for implementations of two nonlinear time series analysis 
models - the Threshold autoregression (TAR) model and the bilinear model. 

I'm particularly interested in implementations for Splus, but enquiries 
seem to suggest that none exist. Maybe you know better...

I'll summarise and post any useful info.

John Mitchell,
Trinity College Dublin,
Ireland.
-----------------------------
mitchllj@vax1.tcd.ie
Newsgroups: sci.math.stat
From: marchett@antares.nosc.mil (Dave Marchette)
Subject: sigma from range
Organization: Naval Ocean Systems Center, San Diego, CA
X-Newsreader: Tin 1.1 PL4
Date: Fri, 20 Nov 1992 16:12:26 GMT

Here's a simple question, I wonder if anyone can help with:

Let x1,...,xn be iid normal 0, sigma, and let x(1),...,x(n)
be the order statistics.  Assume that only n and x(n)-x(1)
are known.  That is, only the number of points and the total
spread of the points is known.  What is the appropriate estimate 
of sigma?

Thanks for any help,

David Marchette
NRaD 
Code 421
San Diego, Ca  92152
marchett@antares.nosc.mil

Newsgroups: sci.math
From: piatko@venus.cs.umbc.edu (Christine Piatko)
Subject: Re: Minimum number of lines that cover a set of points
Summary: NP-complete
Organization: University of Maryland Baltimore Campus, Computer Science Department
Date: Wed, 18 Nov 1992 16:23:10 GMT

> I am looking for an algorithm for the following problem:
> 
>     Given a set P of points in the plane find a minimal 
>     number of straight lines such that every p in P is
>     on at least one of these lines.
> 
>      sauer@nws.e-technik.tu-muenchen.de

Finding the *minimum* number of lines to cover points was shown to
be NP-hard (NP-complete if you ask "Is there a way to cover the
points with k lines?") in the following paper:

\bibitem[MT82]{MT}
N.~Megiddo and A.~Tamir.
\newblock On the complexity of locating linear facilities in the plane.
\newblock {\em Operations Research Letters}, 1(5):194--197, November 1982.

Christine Piatko
piatko@cs.umbc.edu
Newsgroups: sci.math
From: perry@media.mit.edu (Chris Perry)
Subject: Tensor Diagonalization
Organization: MIT Media Laboratory
Date: Fri, 20 Nov 1992 22:14:59 GMT


        I'm wondering if anyone has seen a tensor of rank greater than two
factored into its principle components - i.e., given a tensor A of rank n,
is there a decomposition similiar to
         -1
        S   A S  =  L

  where L is a "diagonal" tensor of rank n, and S is a tensor of rank n that
is built out of the eigentensors (!) of A? Thanks for any advice or
references on this topic -

chris perry
perry@media-lab.mit.edu


Newsgroups: sci.math
From: cjh@tinton.ccur.com (Christopher J. Henrich)
Subject: Magic Squares (was: Re: Sum of Numbers)
Organization: Concurrent Computer Corp., Tinton Falls, NJ
Date: Sat, 14 Nov 1992 23:30:01 GMT

In article <1992Nov12.214936.15458@aio.jsc.nasa.gov> nas_ps@jsc.nasa.gov writes:
>I hope this is not a FAQ.  I have posted the same question on rec.puzzles.
>Given numbers from 1 to 16, arrange them on a 4 by 4 - magic square such that
>when added them diagonally, horizontally, and vertically would yield the same
>number.  Is there any algorithm do this problem ? The solution may not be 
>unique.  Can we use the solution from a simultaneous equations ?
>
There are 880 solutions.  We count two solutions as being the same if
they differ only by a rotation or reflection of the square.  The
algorithm for finding this out is an example of "backtracking."
Here is an outline of how it might start (leaving out clever
details):

Try to find solutions with, say, a "1" in the upper left hand
corner.  So, place a "1" there; now try to find solutions by placing
a "2" next to the "1".  so far so good, it seems... let's try placing
"3" in the next square over.  It won't do.  To make the top
row add up to 34, you would need to put "28" in the upper right,
and the available numbers go up only to 16. So, *backtrack* -
erase the "3" and try a "4".  And so on.

This is clearly a job for a computer.  In the seventeenth century,
a French mathematician named Frenicle (^ over the first "e")
did it by hand.  Others have implemented it by computer.

See also my paper on magic squares and linear algebra, in the 
_American Mathematical Monthly_, June-July 1991.

Regards,
Chris Henrich
Newsgroups: sci.math
From: asimov@wk223.nas.nasa.gov (Daniel A. Asimov)
Subject: Re: A Question About Fundamental Group
Organization: NASA Ames Research Center
Date: Thu, 19 Nov 92 18:37:30 GMT

In article <1992Nov19.002727.2848@galois.mit.edu>, jbaez@riesz.mit.edu (John C. Baez) writes:
|> In article <amirishs.722059588@acf9> amirishs@acf9.nyu.edu (shaahin amiri sharifi) writes:
|> >Consider a bunch of infinitely many (countable) circles with a
|> >point in common. The radii of these circles make a sequence like
|> >{1/n}. What is the fundamental group of this space? Any comments
|> >or referenc would be so helpful!
|> 
|> This space is called the Hawaiian earring space.  I don't recall any
|> references to it - perhaps in the book Counterexamples in Topology?

In his Lectures on Algebraic Topology (Benjamin), Marvin Greenberg cites
this space as an example of a space which fails to be semi-locally simply
connected, and consequently it is a space which has no universal covering
space.

(Definition:  A space X is semi-locally simply connected if for any x in X,
there is a neighborhood U of x such that any loop in U based at x can be
shrunk in X to the point x.)  Greenberg shows that this is a necessary condition
for a space to possess a universal covering space.

Dan Asimov
Mail Stop T045-1
NASA Ames Research Center
Moffett Field, CA 94035-1000

asimov@nas.nasa.gov
(415) 604-4799
From: edgar@function.mps.ohio-state.edu (Gerald Edgar)
Newsgroups: sci.math
Subject: Re: help me take a derivative of this complex function
Date: 17 Nov 1992 14:20:07 -0500
Organization: The Ohio State University, Dept. of Math.
Distribution: usa
NNTP-Posting-Host: function.mps.ohio-state.edu

f(x+i*y) = y + i*x.

>Since the function f(z) = u(x,y) + iv(x,y)   (where z=x+iy)
>does NOT satisfy the second Cauchy-Riemann equation, it is not differentiable
>(as a complex function).  So f'(z) does not exist.

Do you need the derivative (which does not exist) or the absolute value
of the derivative (to test for behavior of the dynamical system)?
The function in question preserves distances,
|f(z1)-f(z2)| = |z1-z2|, so use 1 for the "absolute value of the derivative".

-- 
  Gerald A. Edgar                Internet:  edgar@mps.ohio-state.edu
  Department of Mathematics      Bitnet:    EDGAR@OHSTPY
  The Ohio State University      telephone: 614-292-0395 (Office)
  Columbus, OH 43210             -292-4975 (Math. Dept.) -292-1479 (Dept. Fax)
Newsgroups: sci.math