HDTenEightyP/NetNews huggingface dataset:
From: mramesh@cbnewse.cb.att.com (m.ramesh)
Subject: Use of Statistical Techniques in Stock Selection
Organization: AT&T
Distribution: na
Date: Tue, 13 Oct 1992 19:43:21 GMT
Followup-To: poster


Has anyone ever used statistical analysis such as regression, correlation,
forecasting, ectc on stock for investment puposes.  Is there any book which
talks about this.

I have searched enough I could not find any book wich uses statistical analysis
for analysisng stocks, mutual funds, etc.  

Why is it not popular?

I would also be interested in software for PC to do statistical analysis.
It should be able to do graphics, forecasting, regression, etc.  prefereably
for windows.

I know metastock does some of this but not real forecasting.  I may be
wrong there.

Ramesh

Newsgroups: sci.math.stat
From: bickis@skmath3 (M. Bickis)
Subject: Re: Rational functions: a linear model?
Organization: University of Saskatchewan, Saskatoon, Canada
Date: Wed, 14 Oct 1992 18:34:04 GMT

>In article <1992Oct11.153538.12821@zip.eecs.umich.edu> ayman@eecs.umich.edu 
(Ayman I. Kayssi) writes:
>>I'm trying to fit data to a rational function. 

John Nelder wrote a paper in the '60's about inverse polynomial regression that
might give you the sort of fit you need.  I can't recall the exact reference,
but it is discussed in McCullagh & Nelder's "Generalized Linear Models".

>What is the transformation that I need to make to have a linear model?

Can't be done.  That's why you need a generalized linear model.


>>>>>>>>>>>>>>>>>>>bickis@math.usask.ca<<<<<<<<<<<<<<<<<<<<<<<<<<<
Mik Bickis       \,,,       .*#*.  \    University of Saskatchewan
Department of        \,,,  ^\\|//^  ```\   Saskatoon, Saskatchewan
Mathematics & Statistics \   )|(        ```\   Canada      S7N 0W0
<<<<<<<<<<<<<<<<<<<S|A|S|K|A|T|C|H|E|W|A|N|>>>>>>>>>>>>>>>>>>>>>>>

Xref: sparky sci.math.stat:2151 sci.math.num-analysis:3035
From: psjmt@cc.flinders.edu.au (<J.Tizard> Psychology x2420)
Newsgroups: sci.math.stat,sci.math.num-analysis
Subject: Looking for Multidemnsional Scaling Code
Date: 15 Oct 92 00:39:59 GMT
Organization: Flinders University

I am looking for code (pref C, but anything will be appreciated) to
do Multi-Dimensional Scaling and/or Multidimensional Similarity Structure
Analysis. Any suggestions gratefully appreciated...

thanks in advance

-----------------------------------------------------------------------
 _--_|\        James Tizard                             
/      \       Cognitive Neuroscience Laboratory
\_.-*._/       Psychology Department                    
      v        Flinders University of South Australia   
               psjmt@cc.flinders.edu.au
From: euectk@uts.mcc.ac.uk (Thomas Krichel)
Newsgroups: sci.math.stat
Subject: gauss mailing list
Date: 12 Oct 92 17:32:15 GMT
Organization: Manchester Computing Centre, Manchester, England, M13 9PL.

Is there a mailing list for the GAUSS matrix manipulation package?
I tried a 'list global /gauss' to listserv@bitnic, but to no avail.

  ______                               
    /   /                              Department of Economics
   /   /_  ________  __.  _            University of Keele
  /   / /_(_) / / <_(_/|_/_)           ST5 5BG                         
    _   ,                  _           Great Britain          
   ' ) /           /      //           Tel.: 44 - 782 - 583091  
    /-<  __  o _. /_  _  //            Fax:  44 - 782 - 717577
  ./   )/ (_<_(__/ /_</_</_            E-mail: Krichel@uts.mcc.ac.uk
From: jerry@hnrc.tufts.edu (Jerry Dallal)
Newsgroups: sci.math.stat
Subject: Re: Are blocks fixed or random effects?
Date: 16 Oct 92 17:13:08 GMT
Organization: USDA HNRC at Tufts University

In article <1992Oct15.184712.9572@vax.oxford.ac.uk>, jnewman@vax.oxford.ac.uk writes:
> 
> (1) Are there times in which blocks are clearly fixed effects and
> times in which they are clearly random effects? 

Yes. You stated the conditions.  It depends on how you want to generalize.
In my experience, they're almost always random.

> 
> Following up on this are two questions relating to the case in which
> blocks are considered random effects: 
> 
> (2) Agricultural experimental design texts tend to recommend
> purposefully confounding the interaction and the subjects within
> treatments term by having only a single subject per treatment by
> block combination. This circumvents the issue of whether blocks are
> fixed or random effects because only one possible error term exists.
> Why is it `correct' to assume no interaction term in this case but not
> when the design is not confounded?  Or, is it always our option to
> forget about the A*B interaction and use an error term with 85 df? 
> 

I'm not completely clear on what this says.  In agricultural randomized 
blocks experiments there is one observation per combination of treatment
and block, so the error term is the block*treatment interaction.

Do *not* forget about the interaction unless you've got good reason to do so.

> (3) If the A*B interaction is included in the model but not found to
> be significant, can we substitute the subjects within treatment term
> in forming the F ratio? 
> 

Do *not* pool unless you've got good reason to do so.  You could try the
analysis both ways.  If pooling makes a difference, be wary. In theory,
pooling in the absence of an interaction only increases your error df.  They've
got to be small to begin with for pooling to matter.

Also, be wary of any technique that applies a significant test conditionally
on the results of a prior test.

Sorry for the "sound bite" answers but, as you've alredy noted, entire
textbooks can be written about these issues.



> Thank you in advance for taking the time to answer these questions.
> 
> Jonathan Newman			Joy Bergelson
> Dept. of Zoology		Dept. of Biology
> University of Oxford, UK	Washington University, USA
Newsgroups: sci.math.stat
Subject: Help with a problem...
From: ytakahashi@eagle.wesleyan.edu
Date: 11 Oct 92 17:27:56 EDT
Organization: Wesleyan University

Perhaps someone can help me out...

 
	Three people work to solve a problem independantly with differing
chances of solving it.  Given these probabilities, what is the probability
that the problem is solved?
 
 
Since they are independent, P(AB) = P(A)*P(B)  by definition
I extended this to... P(ABC) = P(A)*P(B)*P(C)
	(I'm not sure if that's legal to do)
P(AUBUC) = P(A)+P(B)+P(C) - P(ABC)   by definition
 
plug in from above yields...
P(AUBUC) = P(A)+P(B)+P(C) - P(A)*P(B)*P(C)
 
Is P(AUBUC) actually what I am looking for?
 
Did I do anything illegal (mathematically speaking) here?
 
If this is right, then the probability of the problem being solved
is nothing more than the addition of the three individual probabilities
minus their product.  Right?
 
Any help is greatly appreciated. 

				- Yuki

please followup to this as my mail server has been unreliable.

Newsgroups: sci.math.stat
From: news@massey.ac.nz (USENET News System)
Subject: Re: Goodness of Fit with Zero Degrees of Freedom
Organization: Massey University
Date: Thu, 8 Oct 92 22:37:56 GMT

In article <1b2156INNnnf@roundup.crhc.uiuc.edu>, hougen@vision.csl.uiuc.edu (Darrell Roy Hougen) writes:
> 
> chaas@coe.drexel.edu (Chuck Haas) writes:
> 
> 
> *>Suppose I have a set of categorical data.
> ...
> *> If the model has k parameters and there are m groups, then I know
> *>that I could do a goodness of fit test (e.g., Fisher chi-square or
> *>likelihood ratio) and compare to the chi-square distribution with m-k
> *>degrees of freedom.
> 
> I'm not sure I understand your problem, but shouldn't the number of
> degrees of freedom be equal to the number of data rather than the
> number of categories?
> 
No, however the parameters should be estimated from the _grouped_
data. See Conover "Non-parametric Statistics" (or some-such title)
Newsgroups: sci.math.stat
From: wskelly@laurel.ocs.mq.edu.au (William Skelly)
Subject: Re: least squares fit to function
Organization: Macquarie University, Australia.
Date: Wed, 14 Oct 1992 02:02:28 GMT

In article <1992Oct13.151606.8435@cbfsb.cb.att.com> rizzo@cbnewsf.cb.att.com (anthony.r.rizzo) writes:
>Some time ago, I asked for net-wisdom on the subject of constrained
>least squares.  Many of you responded, letting me know that I was
>on track.  First, let me thank all those who responded.  I've since
>written my own little program to do constrained least square fits
>of n-degree polynomials.  But now I have a slightly off-the-wall
>question for you.  Read on. ;-)
>
>Given some explicitely defined function g(x), say, g(x) = sin(x),
>can the method of least square errors be applied such that
>we derive a second function f(x) = a0 + a1*x + a2*x^2 + ... + an*x^n  
>where f(x) is the best least squares fit to g(x)?
>
>I know that this request sounds strange.  But I have a legitimate
>application.  The application software that I'm using, ANSYS, 
>forces me to input certain quantities as polynomial functions
>of temperature.  So I can't get around using a polynomial.
>Given this restriction, I at least want to use a best-fit polynomial.
>
>Has anyone ever heard of this being done before?
>
>Tony Rizzo
>

Yes. I think you want to check out Generalised Least-Squares
fitting routines.  I am currently using the one in Numerical 
recipes for which fitting a polynomial is straightforward.
Press et al. recommend their singular value decomposition
over least-squares or weighted least-squares routines.

If you figure out how to use it you might let me know how
I can find the best fit for a spherical variogram using these
routines ;-).  

Cheers,
Chris
From: jira@latcs1.lat.oz.au (Ajin Jirachiefpattana)
Newsgroups: sci.math.stat
Subject: Help for Stochastic Activity Networks.
Date: 16 Oct 92 12:52:43 GMT
Organization: Comp Sci, La Trobe Uni, Australia


Hi everybody,

This may not be the appropriate news group (if not, can someone point me
in the right direction?) but ..

Does anyone out there know of Stochastic Activity Networks (SAN),
general comments on a comparison of Stochastic Activity Networks to
Stochastic Petri Nets (SPN)? Why is it not widely used like Stochastic 
Petri Nets (this is my opinion that may be not correct)? Is there any 
software tool for analysis, simulation and evaluation the Stochastic 
Activity Networks available in the public domain? 

Any help is greatly appreciated.

Ajin Jirachiefpattana,
jira@latcs1.lat.oz.au

Department of Computer Science & Computer Engineering,
La Trobe University,
Bundoora, Vic., 3083.
Australia.
Newsgroups: sci.math.stat,sci.math.num-analysis
From: charlie@umnstat.stat.umn.edu (Charles Geyer)
Subject: random numbers on a Cray
Organization: School of Statistics, University of Minnesota
Date: Sat, 10 Oct 1992 15:31:28 GMT

Dumb novice question about Cray Fortran.  Can anyone tell me whether the
built-in random number generator RANF is o. k. to use?

-- 
Charles Geyer
School of Statistics
University of Minnesota
charlie@umnstat.stat.umn.edu
Xref: sparky sci.math.stat:2098 sci.math.num-analysis:2970
From: fmontoya@frors65.circe.fr (frederic montoya)
Newsgroups: sci.math.stat,sci.math.num-analysis
Subject: Re: Gibbs sampling and annealing (was: Help!  Book recommendations?)
Date: 9 Oct 92 11:50:16 GMT
Reply-To: fmontoya@frors65.circe.fr (frederic montoya)
Organization: circe

In article <1992Oct4.192217.27919@news2.cis.umn.edu>,
charlie@umnstat.stat.umn.edu (Charles Geyer) writes:
> In article <1992Oct3.210337.21498@news2.cis.umn.edu> I wrote:
> 
>    It makes no sense to compare Gibbs sampling versus simulated annealing, 
>    for example.
> 
> In article <92Oct4.130952edt.243@neuron.ai.toronto.edu>
radford@cs.toronto.edu
> (Radford Neal) replies:
> 
> > Correct, but not for the reasons you perhaps mean. Simulated annealing
> > is a technique that can be used in conjunction with Gibbs sampling 
> > (or other Markov chain methods, such as the Metropolis algorithm) 
> > in order to reach the final equilibrium distribution more quickly.
> 
> Depends on how you think about Markov chain Monte Carlo.  The
> Metropolis-Hastings algorithm produces a Markov chain with a known
> stationary distribution.  This "annealing trick" doesn't.  So far
> from mixing MCMC and simulated annealing, it is not MCMC at all.
> 
> Are there any practically useful convergence results for such schemes
> once Markov chain theory is thrown out the window?
> 

This especially true whenever you want to sample thermodynamic
quantities. Averages must then be well controlled in order
to get significant results.

-----
Frederic Montoya
LSG2M - Ecole des Mines
fmontoya@circe.fr
Newsgroups: sci.math.stat,sci.math.num-analysis
From: jja@fnbc.com (Joseph Alotta)
Subject: Re: Help!  Book recommendations?
Organization: First National Bank Of Chicago, Chicago IL, USA
Date: Fri, 9 Oct 92 15:40:16 GMT

>  Can anyone recommend some good books on the follwing:
> 
> [3] Simulated annealing
> 

numerical recipes in c, press, et al, cambridge university press, is  
available widely and has a very good section on SA.

even i can undestand it.

joe.

--
==============================================================
! joe alotta                                    jja@fnbc.com !                                               
!                                             (312) 732-3439 !
!                                                            !
! "The main thing is to keep the main thing the main thing." !
! Dr. George Sweeney                                         !
==============================================================
From: scott@gw.wmich.edu
Newsgroups: sci.math.stat
Subject: Latin Hyper Cube Simulation
Date: 12 Oct 92 16:31:41 EST
Organization: Western Michigan University

Has anyone heard of simulation using a method called Latin
Hyper Cube?  How does this differ from Monte Carlo?

Julie Scott
University Computing Services
Western Michigan University
Kalamazoo, MI  

scott@mickey.acs.wmich.edu
Newsgroups: sci.math.stat
From: dclason@dante.nmsu.edu (Dennis Clason)
Subject: Re: approx. of binomial dist., help needed
Organization: New Mexico State University, Las Cruces, NM
Date: Tue, 13 Oct 1992 15:21:11 GMT

In article <1992Oct8.202310.10461@ultb.isc.rit.edu> jsvrc@rc.rit.edu (J A Stephen Viggiano) writes:
>In article <1992Oct7.025857.28031@news2.cis.umn.edu> lee@hecto.cs.umn.edu (YoungJun Lee) writes:
>>
>> The stat. book I have just says that
>>  "Binomial distribution with n trials and success probability p can be
>>   approximated by possion distribution(when n is large, p is very small, and
>>   np is of moderate magnitude" and normal distribution(when n is large and
>>   p is not too near 0 or 1)"
>
>For the Poisson approximation, it is much more important for p to be small
>than it is for n to be large. The approximation is quite acceptable for n = 1
>with p <= 0.01. This can be seen by looking at the relative error in the
>variance; it involves only p.
>

Strictly speaking, the approximation is based on the fact that the
a sequence of binomial random variables converges in distribution
to a Poisson if n --> inf and p --> 0 in such a way that np --> lambda.
So, it's not so much that it's important for p to be small as it is that
np be small relative to n.  In other words, the mass function has to be
stacked up near 0.

I ought to pay small extra today because I'm working it so hard.
Newsgroups: sci.math.stat
Subject: Re: approx. of binomial dist., help needed
From: news@massey.ac.nz (USENET News System)
Date: Sun, 11 Oct 92 21:32:03 GMT
Organization: Massey University

In article <1992Oct8.202310.10461@ultb.isc.rit.edu>, jsvrc@rc.rit.edu (J A Stephen Viggiano) writes:
> 
> For the gaussian approximation, we were taught that the tails of the
> approximating distribution should be well within the limits of 0 and n. Thus,
> np - 5 (npq)**0.5 should be greater than zero, and np + 5(npq)**0.5 should
> be less than n, where q = 1 - p. In other words, the mean should be at least
> five standard deviations from both zero and n. Again, this is a rule of
> thumb. For p = 0.5 (the best case), n should be at least 25. Smaller or
> larger values of p will require a larger n to reduce the coefficient of
> variation.
> 
It is interesting to see the diversity of opinions in the text books on this.
Ott and Mendenhall even give two different rules in the same book! At
on place they say we need np > 5 and n(1-p) > 5 and elsewhere they say
np^ > 10 and n(1-p^) > 10. The first rule seems to be for calculating
binomial probabilities with p known, and the latter for inference when
p is unknown. They do not draw the student's attention to the apparent
discrepancy.
Larsen and Marx give a rule more like the one quoted above, except they
are far less conservative. They only require
np^ - 2 (np^q^)**0.5 > 0, and np^ + 2 (np^q^)**0.5 < n.
O & M's second suggestion is equivalent to
n > max(10/p^, 10/q^)
while L & M's is
n > max(a^2*p^/(1-p^), a^2*q^/(1-q^)) where a = 2.
Taking different values for a gives a host of possible rules and leaves
scope for adjusting a to suit the size of confidence interval we wish
to use. Taking a = 5 gives roughly the n > max(5/p, 5/q) rule.

Terry Moore
From: jnewman@vax.oxford.ac.uk
Newsgroups: sci.math.stat
Subject: Are blocks fixed or random effects?
Date: 15 Oct 92 17:47:12 GMT
Organization: Oxford University VAX 6620

Consider a two-way anova in which factor A has 4 levels and factor B
has 8 levels and there are 3 replicates per treatment combination.  If
both treatments are fixed effects, then the error term for both main
effects and the interaction is the subjects within treatments term
which has 64 df.  However, if treatment B is a random effect then the
error term for testing A is the A*B interaction with 21 df, this is
sometimes called a mixed model.

Now, what if treatment B is really a blocking factor?  Would B be
considered a fixed or random effect.  According to some psychology
texts on the subject (e.g. Edwards: Experimental Design in
Psychological Research, 5th ed, chapter 16) nearly all blocking
factors must be considered random effects since we wish to draw
inferences about the population of blocks, not just these particular
blocks.  On the other hand, experimental design texts in the
agricultural field never mention the fact that blocks might be random
effects.   Our first question is: 

(1) Are there times in which blocks are clearly fixed effects and
times in which they are clearly random effects? 

Following up on this are two questions relating to the case in which
blocks are considered random effects: 

(2) Agricultural experimental design texts tend to recommend
purposefully confounding the interaction and the subjects within
treatments term by having only a single subject per treatment by
block combination. This circumvents the issue of whether blocks are
fixed or random effects because only one possible error term exists.
Why is it `correct' to assume no interaction term in this case but not
when the design is not confounded?  Or, is it always our option to
forget about the A*B interaction and use an error term with 85 df? 

(3) If the A*B interaction is included in the model but not found to
be significant, can we substitute the subjects within treatment term
in forming the F ratio? 

Thank you in advance for taking the time to answer these questions.

Jonathan Newman			Joy Bergelson
Dept. of Zoology		Dept. of Biology
University of Oxford, UK	Washington University, USA
Newsgroups: sci.math.stat
From: rizzo@cbnewsf.cb.att.com (anthony.r.rizzo)
Subject: least squares fit to function
Organization: AT&T
Date: Tue, 13 Oct 1992 15:16:06 GMT

Some time ago, I asked for net-wisdom on the subject of constrained
least squares.  Many of you responded, letting me know that I was
on track.  First, let me thank all those who responded.  I've since
written my own little program to do constrained least square fits
of n-degree polynomials.  But now I have a slightly off-the-wall
question for you.  Read on. ;-)

Given some explicitely defined function g(x), say, g(x) = sin(x),
can the method of least square errors be applied such that
we derive a second function f(x) = a0 + a1*x + a2*x^2 + ... + an*x^n  
where f(x) is the best least squares fit to g(x)?

I know that this request sounds strange.  But I have a legitimate
application.  The application software that I'm using, ANSYS, 
forces me to input certain quantities as polynomial functions
of temperature.  So I can't get around using a polynomial.
Given this restriction, I at least want to use a best-fit polynomial.

Has anyone ever heard of this being done before?

Tony Rizzo
From: rhh@alice.att.com (r hardin)
Newsgroups: sci.math.stat
Subject: Re: Use of Statistical Techniques in Stock Selection
Date: 13 Oct 92 23:47:23 GMT
Article-I.D.: alice.23881
Organization: AT&T Bell Laboratories, Murray Hill NJ


m.ramesh writes:
>Has anyone ever used statistical analysis such as regression, correlation,
>forecasting, ectc on stock for investment puposes.  Is there any book which
>talks about this.

People used to find cycles by weighting price histories with secret
weights, I think in the '50s.  Somebody spoiled a lot of the fun
by analyzing the spectrum of the weighting functions.

``A Random Walk Down Wall Street'' is still a the best book, if you're
inclined to think statistical techniques might help.  It ought to
dissuade you.
From: jsvrc@rc.rit.edu (J A Stephen Viggiano)
Subject: Re: approx. of binomial dist., help needed
Organization: RIT Research Corp
Date: Thu, 15 Oct 1992 14:19:53 GMT

In article <1992Oct13.152111.19443@nmsu.edu> dclason@dante.nmsu.edu (Dennis Clason) writes:

>Strictly speaking, the approximation is based on the fact that the
>a sequence of binomial random variables converges in distribution
>to a Poisson if n --> inf and p --> 0 in such a way that np --> lambda.

Most people select the value of lambda to be *precisely* np. They match the
first moment.

>So, it's not so much that it's important for p to be small as it is that
>np be small relative to n.

Which is essentially the same as saying (as I did in an earlier post) that
it's important for p to be small. How can np be small relative to n, without
p being small????? Am I missing something?
From: fsmgs@camelot.acf-lab.alaska.edu (Michael Schmahl [Black-Robe Mage])
Subject: Re: Mattel says "Math is tough."
Organization: University of Alaska Computer Network
Date: Thu, 8 Oct 1992 00:13:01 GMT

Cameron Randale Bass writes
>      Try teaching multiplication to a seven-year-old.  That way, 
>      you get to see how 'hard' it is from both sides.

As a person who once was seven years old, I would like to say that I never  
found multiplication hard, except for seven times six and seven times eight.   
I could multiply and do long division since I was five.
From: rabjab@golem.ucsd.edu (Jeff Bytof)
Newsgroups: sci.math
Subject: Talking Ken: "Math class is easy!" ?
Date: 9 Oct 92 00:57:59 GMT
Organization: ucsd
NNTP-Posting-Host: lutherlab.ucsd.edu

Boy, that would stir 'em up!

--------
rabjab@golem.ucsd.edu
From: fsmgs@camelot.acf-lab.alaska.edu (Michael Schmahl [Black-Robe Mage])
Newsgroups: sci.math
Subject: Re: Info needed on graphing calculators
Date: 15 Oct 92 02:47:19 GMT
Article-I.D.: raven.1992Oct15.024719.13289
Organization: University of Alaska Computer Network

ROBB SCHECTER writes
> I am about to buy the -expensive- HP 48sx.  I've got one of HP's older
>    RPN models, and I love it.   This is the main reason I think Im
>    going to get HP again.  Also I think the HP48s and 48sx are the
>    only two RPN ones out there.

I recently bought one of these and I must say it is a good deal.  It doesn't  
work algebraically with vectors, but it can be taught.  However there are  
other graphing calculators out there.  You might want to look into the 21S,  
for example.  A friend of mine had one of these and it has satisfied his  
needs.  However, I do believe it is more expensive than the 48SX.  The 48SX  
works well with matrices and statistics and has a wide variety of ufnctions  
and is easilly programmed.  I believe it to be worth the $250 or whatever  
you end up paying for it.
Newsgroups: sci.math