HDTenEightyP/NetNews huggingface dataset:
From: paul@music.sie.arizona.edu (Paul J. Sanchez)
Newsgroups: sci.math.stat
Subject: Re: random number generator
Date: 27 Jul 92 20:12:30 GMT
Organization: University of Arizona UNIX Users Group

Jerry Dallal writes
> In article <1992Jul27.124120.29511@cl.cam.ac.uk>, nmm@cl.cam.ac.uk (Nick  
Maclaren) writes:
> > In article <1992Jul27.103659.11820@kth.se>, md87-mpe@hemul.nada.kth.se
> > (Magnus Pettersson) writes:
> >  
> > |> 3. G.E.P.Box and M.E.Mueller
> > |>    A Note on the Generation  of Random Normal Deviates
> > |>    Ann.Math.Stat. (1958) 29, 610-611
> > 
> > Don't use this method in single precision [...]
> > 
> 
> Wait! . . .  Stop! . . . Hold on a moment! . . .
> 
> There is nothing wrong with the Box-Muller method.  It is
> theoretically sound [...]

Theory works beautifully when all of the assumptions hold.  One of the  
assumptions for the Box-Muller method is that you have i.i.d. uniform  
variables on the input side.  This happens to be false in most computing  
contexts -- most people use a sequence of pseudo-random numbers which are  
uncorrelated but hardly independent.

The most common source of pseudo-random numbers is the Linear Congruential  
Generator algorithm, or LCG for short.  A result by Marsaglia states that  
k-tuples from a LCG all fall on a bounded number of hyperplanes.  As a  
result, there is an interaction with the Box-Muller algorithm which causes  
all of the values produced to fall along a spiral.  For some very pretty  
pictures, check out the book "Stochastic Simulation" by Brian D. Ripley  
('87, J. Wiley & Sons).  Pages 55-58 should do a good job of convincing  
you that the results are definitely not independent normals.

There are a couple of morals to this story:
a) If you want to use Box-Muller, use something other than a LCG; and
b) Just because an algorithm is theoretically sound, don't assume you'll  
get usable results.

--paul
paul@music.sie.arizona.edu
(NeXT mail welcome!)
From: jb1556@swuts.sbc.com (Jim Buddenhagen)
Newsgroups: sci.math.stat
Subject: random number generator
Keywords: pseudo-random, C , uniform, normal
Date: 25 Jul 92 14:50:11 GMT
Organization: Southwestern Bell Telephone Company

Portable pseudo-random number generator desired, for uniform and/or normal
deviates.  What is desired is code (C preferred) or algorithm that is
machine independent (i.e. same seed, same sequence regardless of computing
platform).  Purpose will be to generate random datasets (or pointers into
databases) for benchmark tests accross several platforms.  Must be able to
generate several independent sequences 'simultaneously' (ok to have several
copies of routine with different names).  

I am aware of routines in Numerical Recipies, and in Knuth, but unsure
of quality.  Would welcome any comments, suggestions, pointers to code,
or references.

-- 
Jim Buddenhagen             Southwestern Bell Telephone Co.
jb1556@swuts.sbc.com        Statistical Research
314-235-5183                One Bell Center, Room 27-X-5
                            St. Louis, MO 63130
From: rja14@cl.cam.ac.uk (Ross Anderson)
Newsgroups: sci.math.stat
Subject: Re: random number generator
Date: 28 Jul 92 13:31:48 GMT
Reply-To: rja14@cl.cam.ac.uk (Ross Anderson)
Organization: U of Cambridge Computer Lab, UK

An enormous amount has been done on this subject by the cryptological
fraternity. In fact, most cryptosystems in use outside the banking world
seem to work by applying a pseudo-random number stream to the plaintext.

Suggestion: if you want a really good random number generator for stats
work, just encrypt a counter using the DES algorithm. If you can find
anything statistically wrong with this, then you'll be famous (if the
spooks don't get to you first).

Ross Anderson
Cambridge University Computer Laboratory
rja14@cl.cam.ac.uk
+44.223.334676
From: horn@schaefer.math.wisc.edu (Jeffrey Horn)
Newsgroups: sci.math.stat
Subject: Best Subset with Non-Divisible Y-data
Date: 21 Jul 92 17:56:57 GMT
Organization: Univ. of Wisconsin Dept. of Mathematics

I would like to do similar analysis to a "best subset search" for regression
models (methods include regression by leaps and bounds, forward/backward
selection, all subsets, etc.) for which is "non-divisible".  By this I mean
that one can rank the values of the independent and/or dependent variables
from 1 to N, but a ranking of 2 is NOT TWICE BIG AS A ONE, etc.  Some of
the models I am looking at actually have mixtures of divisible and non-divisible
independent variables.  I am also looking at models in which the dependent
variable is either non-divisible or divisible.  I want to find something
analogous to regression for these kinds of models.  I am sure that any method
that can be dug up will be less powerful than regression.

Is there any method to handle such models?

Jeff Horn
From: nichols@spss.com (David Nichols)
Subject: Re: Greenhouse-Geisser Correction Algorithm Needed
Date: Fri, 24 Jul 1992 20:49:40 CUT
Organization: SPSS Inc.

The formula for the Greenhouse-Geiser epsilon for a within subjects effect
(main effect or interaction), from the MANOVA chapter in the SPSS Statistical
Algorithms, 2nd ed. is:

                          2
              (trace(SSE))
 epsilon = -------------------
                           2
            k * trace((SSE) )

where k =  degrees of freedom for the factor or interaction
      SSE = Error SSCP matrix for that effect

In other words, on top you're getting the trace and then squaring it. On
the bottom you're squaring the SSE matrix, then taking the trace and
multiplying it by k. I checked this out running an example in MANOVA,
and the formula gives the same results as MANOVA does.

--
 David Nichols           Statistical Support Specialist            SPSS, Inc.
 Phone: (312) 329-3684     Internet: nichols@spss.com     Fax: (312) 329-3657
*******************************************************************************
 Any correlation between my views and those of SPSS is strictly due to chance.
Newsgroups: sci.math.stat
From: winzar@csuvax1.murdoch.edu.au (Hume Winzar)
Subject: Re: Logistic Regression Program
Organization: Commerce, Murdoch University
Date: Tue, 28 Jul 92 02:08:13 GMT

In article <Bs1x10.Eyu@zoo.toronto.edu> jackson@zoo.toronto.edu (Donald Jackson) writes:
>From: jackson@zoo.toronto.edu (Donald Jackson)

>I am trying to track down a routine for calculating logistic
>regression based on a maximum likelihood approach.  I'd appreciate it
>if anyone could point to a source, preferably in FORTRAN.

Try BLOGIT: a routine designed for Multinomial logit modelling.  It's 
discussed in Hensher, D.A. and Johnson, L.W. (1981) "Applied Discrete 
Choice Modelling," published by Croom Helm in London and by John Wiley & 
Sons in New York.  It's also to be found in Crittle, F.J. and Johnson, L.W. (
1981) "BLOGIT: A Program for Estimation of Multinomial Logit Choice 
Models," *Journal of Marketing Research* 18,4, pp.483-484.

The original programme has been "lifted" several times to produce some 
commercially available programmes with nice user-friendly front ends (Sorry 
I don't know any names.)  The fortran source code and a version compiled for 
PC seems to be around many faculties interested in Transport Economics and/ 
or Marketing Science.  If you have trouble locating these, then e_mail me 
and I'll see if I can find my copies.

  - - - - - - - - -
 |      _--_|\     |   Hume Winzar
 |     /      \    |   Commerce School,
 |     *_.--._/    |   Murdoch University,
 |           v     |   Perth, Western Australia
  - - - - - - - - -  
                       E_Mail winzar@csuvax1.csu.murdoch.edu.au
                       Phone: (09) 310 7389
                       Fax:   (09) 310 5004
Newsgroups: sci.math.stat
From: bassin@wsuaix.csc.wsu.edu (Ed Bassin - Sociology;S23679)
Subject: principal components with autocorrelation
Organization: Washington State University
Date: Wed, 29 Jul 92 17:04:46 GMT

I need a reference (and hopefully some software) for computing principal
components wiht autocorrelated (panel) data.  If anyone knows of such a 
citation, I would be very appreciative.  Thanks.

Ed Bassin
Newsgroups: sci.math.stat
From: H.Edwards@massey.ac.nz (H. Edwards)
Subject: Two positions in stochastic OR and Statistics
Organization: Massey University, Palmerston North, New Zealand
X-Reader: NETNEWS/PC Version 2c
Date: Tue, 28 Jul 92 04:32:09 GMT

Massey University, Palmerston North, New Zealand.
Department of Statistics

Lectureship in Operations Research, and Lectureship/Senior Lectureship in
Statistics.

The Department of Statistics has two newly created positions in Operations
Research and Statistics.  Applicants should have a PhD and/or teaching,
research or consulting experience in one of these areas.  The Department is
particularly interested in seeking candidates with expertise in one or more
of the following: Stochastic Operations Research (applied probability,
decision theory), Business Statistics (statistical process control, total
quality improvement methods), and Applied Statistics (including statistical
consulting).  The Department teaches undergraduate postgraduate and service
courses, and supervises research degrees to the PhD level.  Courses are also
taught by correspondence throughout New Zealand.  The Department is interested
in expanding its consulting activities, and the position in Statistics may be
offered at Senior Lecturer level to a suitably qualified and experienced
applicant.

Further information on teaching and research in the Department may be obtained
from the Head of Department, Professor Jeffrey J Hunter (Phone: 64 6 350-5082,
Fax: 64 6 350-5611, E-mail: J.Hunter@massey.ac.nz).
Reference number 51 (O.R.) or 52 (Statistics) must be quoted.

Closing date:  15 September 1992.

Further details of these positions together with Conditions of Appointment
are obtainable from Mrs V B Bretherton, Personnel Section, to whom
applications, including a full curriculum vitae and the names, addresses and
fax numbers of three referees, should be sent.
-- 


Howard Edwards				Ph: (64)(6)3569099 ext 8331
Dept of Statistics			Fax: (64)(6)3505611
Massey University			email: H.Edwards@massey.ac.nz
Palmerston North
NEW ZEALAND
From: nmm@cl.cam.ac.uk (Nick Maclaren)
Newsgroups: sci.math.stat
Subject: Re: C source for Park-Miller "minimal std. generator":
Keywords: pseudo-random, C , uniform, normal
Date: 27 Jul 92 09:11:10 GMT
Reply-To: nmm@cl.cam.ac.uk (Nick Maclaren)
Organization: U of Cambridge Computer Lab, UK

In article <l73ggjINNh52@almaak.usc.edu>, ajayshah@almaak.usc.edu (Ajay
Shah) writes:
|> #include <stdio.h>
|> 
|> /* This file implements the "minimal standard" RNG
|>    from the paper "RNGs: Good Ones are Hard to Find" by Park and
|>    Miller, CACM, Volume 31, Number 10, October 1988. */
|>
|> ...

PLEASE, PLEASE don't use this generator for serious work (i.e. any project
which uses more than a million numbers or so IN ALL) without checking!

Park and Miller's paper is quite good, but is rather optimistic in their
ideas of what is a minimal reliable generator.  Unfortunately, the same is
true of Marsaglia's (with co-authors) papers "Towards a Universal Random
Number Generator" and "A Random Number Generator for PCs", and Marsaglia
is one of the people who lead this field!  Good RNGs are very, very hard to
find.

Any generator which EITHER has a 32-bit seed OR is based on conventional
single-precision starts to give seriously misleading results for sequences
of a few million numbers.  See N.M. Maclaren "A Limit of the Usable Length
of a Pseudo-random Sequence" J.Statist.Comput.Simul. 42 pp 47-54 for the
proof of the first statement - the proof of the second is trivial to derive
using the same techniques, because of the 24-bit precision limit.

Nick Maclaren
University of Cambridge Computer Laboratory,
New Museums Site, Pembroke Street,
Cambridge CB2 3QG, England.
Email:  nmm@cl.cam.ac.uk
Tel.:   +44 223 334761
Fax:    +44 223 334679
From: sljbr@cc.usu.edu
Newsgroups: sci.math.stat
Subject: NONPARAMETRIC DENSITY ESTIMATION!!
Date: 29 Jul 92 01:07:24 MDT
Organization: Utah State University

hi!,
Could someone give me references regarding bandwidth selection in the
case of descrete and continuous variables (in nonparametric density
estimation using kernels).
Thanks
balaji rajagopalan
From: jerry@ginger.hnrc.tufts.edu (Jerry Dallal)
Newsgroups: sci.math.stat
Subject: Re: random number generator
Date: 27 Jul 92 18:25:07 GMT
Organization: USDA HNRC at Tufts University

In article <1992Jul27.124120.29511@cl.cam.ac.uk>, nmm@cl.cam.ac.uk (Nick Maclaren) writes:
> In article <1992Jul27.103659.11820@kth.se>, md87-mpe@hemul.nada.kth.se
> (Magnus Pettersson) writes:
>  
> |> 3. G.E.P.Box and M.E.Mueller
> |>    A Note on the Generation  of Random Normal Deviates
> |>    Ann.Math.Stat. (1958) 29, 610-611
> 
> Don't use this method in single precision - it has a very serious
> flaw.  While it is OK in double precision, there are faster and simpler
> methods available (e.g. the Polar Method as described in Knuth).  The
> reference for the flaw is by H.R. Neave round about 1970.
> 
> 
> Nick Maclaren
> University of Cambridge Computer Laboratory,
> New Museums Site, Pembroke Street,
> Cambridge CB2 3QG, England.


Wait! . . .  Stop! . . . Hold on a moment! . . .

There is nothing wrong with the Box-Muller method.  It is theoretically sound
and changing from single precision to double precision isn't going to affect
anything.  (For that matter, it isn't going to effect anything, either!)

The Box-Muller transformation is based on the simple fact of distribution
functions that if U and V are iid U(0,1), then 

                       sqrt(-2 log U) sin (2 pi V)
                       sqrt(-2 log U) cos (2 pi V)

are iid N(0,1).

I don't have the article in front of me but I recall that (as explained in a
followup letter) Neave's argument was flawed.  The problem was with a
uniform random number generator that used too small a modulus and didn't "kick
over" fast enough.  

I agree with Mclaren that the Neave article was published in the 70's.  I
can add that it appeared in Applied Statistics.  The followup letter appear
within the next year or two.  I'll leave it to someone else to look up the
exact references.  

(As a practical matter, I prefer to use the inverse of the standard normal
distribution to generate my random numbers.  I know it is computationally
intensive, but it relieves you from having to worry (as much)
about the joint distribution of values in your pseudo-random number stream.)
Newsgroups: sci.math.stat
From: bharat@cs.uiuc.edu (R. Bharat Rao)
Subject: POinter to MARS/CART
Reply-To: bharat@cs.uiuc.edu
Organization: University of Illinois at Urbana
Date: Fri, 24 Jul 1992 22:04:23 GMT

Is there a version of MARS (and CART) available for anon ftp.

Thanks

Bharat
From: danni@salyko.doit.sub.org (Felix Dannegger)
Newsgroups: sci.math.stat
Subject: hires drivers for s+ ?
Keywords: s+, hires, vga
Date: 29 Jul 92 14:40:02 GMT
Distribution: sci


Is anybody using the S+ for DOS package out there, who might be able to
point me to higher resolution screen drivers ?
The graphics capabilities of this package are quite extensive,
unfortunately, the whole thing is not very satisfactory at 640*480 !
Drivers for SVGA or 8514/a adapters, would be what I had in mind.

Thanks, Felix.
--
--------------------------------------|        _-_      Gauss's first, crude
Felix Dannegger                       |       /   \     approximation of his
Munich, Germany                       |      /     \    distribution.
                                      | -----       -----
Preferred: danni@salyko.doit.sub.org  |
Alternate: Felix.Dannegger@statistik.uni-muenchen.dbp.de
-----------------------------------------------------------------------------
From: aboulang@bbn.com (Albert Boulanger)
Newsgroups: sci.math.stat
Subject: Re: POinter to MARS/CART
Date: 25 Jul 92 20:08:51
Organization: BBN, Cambridge MA
Reply-To: aboulanger@bbn.com
NNTP-Posting-Host: kariba.bbn.com
In-reply-to: bharat@cs.uiuc.edu's message of 24 Jul 92 22:04:23 GMT


In article <Brwynp.Lyu@ux1.cso.uiuc.edu> bharat@cs.uiuc.edu (R. Bharat Rao) writes:


   Is there a version of MARS (and CART) available for anon ftp.


There are versions of ID3, a CART-like tool, in the public domain. MARS
is available on the STSLIB serve at CMU.

Good Luck,
Albert Boulanger
aboulanger@bbn.com
From: macdonald@vax.oxford.ac.uk
Newsgroups: sci.math.stat
Subject: MULTIPLE SLOPE COMPARISONS?
Date: 30 Jul 92 12:04:29 GMT
Organization: Oxford University VAXcluster

Statistical problem: how to do multiple comparisons of 20 bivariate regression
slopes where x is the continuous variable and y is the class variable
ie. populations 1-20

Is anyone able to make a suggestion of how to do this and/or a reference
for such a proceedure.
From: hrubin@pop.stat.purdue.edu (Herman Rubin)
Newsgroups: sci.math.stat
Subject: Re: random number generator
Date: 30 Jul 92 17:16:41 GMT
Organization: Purdue University Statistics Department

In article <1992Jul29.143808.241@nutmeg.hnrc.tufts.edu> jerry@nutmeg.hnrc.tufts.edu (Jerry Dallal) writes:
>In article <55413@mentor.cc.purdue.edu>, hrubin@pop.stat.purdue.edu (Herman Rubin) writes:

>> I would not accept anything with a short seed (say at least several 
>> hundred bytes) as acceptable.  Other than the believed cryptographically
>> strong Shamir and Blum-Miccaeli (sp?) procedures, which are extremely
>> costly, I know of none.  The problem is at least moderate-term independence,
>> and correlations, periods, etc., do not answer the question.


>Two questions of Professor Rubin:

>1) What generator *would* you recommend?

At this time, I would recommend starting with some more-or-less random
source, like the news articles repeatedly added in blocks, and then 
using some long-gap system like 

	x[n] = x[n-460] OP x[n-607]

where OP is exclusive or, or preferably full-word integer add.  On some
machines, one can be done with larger pieces than the other.  There are
others available of this type with longer gaps.

There are several reasons for this; on vector machines, the smaller gap 
to a previous item should be at least the length of the vector register,
and on vector stream machines, the newest item used should have been
stored before it is used.

If one can get a reasonable set of physical random numbers, XOR with them
is a good idea.  The supply is not likely to be enough for the whole job,
so recycling is likely to be necessary.

>2) The last time you generated pseudorandom numbers on a computer, what
>generator did you use?

The last time I did simulation, I do not believe that these procedures
were generally known.  Also, there were timing constraints.  What I used
was a congruential generator, to guarantee uniformity, and I recycled
a binary version of the RAND numbers.  The actual simulation used
2,560,000 exponential and normal random variables, and with the 
quite efficient procedures I used, this required probably less than
5.5 million uniforms.  The RAND numbers were 69,066 words, 0 in the
first 12 bits, and 48 random bits; they were used on a CDC 6500, which
accounts for the peculiar format.

Also, at that time, memory was a major problem, not like the situation
now.
-- 
Herman Rubin, Dept. of Statistics, Purdue Univ., West Lafayette IN47907-1399
Phone: (317)494-6054
hrubin@pop.stat.purdue.edu (Internet, bitnet)  
{purdue,pur-ee}!pop.stat!hrubin(UUCP)
From: nmm@cl.cam.ac.uk (Nick Maclaren)
Newsgroups: sci.math.stat
Subject: Re: random number generator
Keywords: pseudo-random, C , uniform, normal
Date: 27 Jul 92 12:41:20 GMT
Reply-To: nmm@cl.cam.ac.uk (Nick Maclaren)
Organization: U of Cambridge Computer Lab, UK

In article <1992Jul27.103659.11820@kth.se>, md87-mpe@hemul.nada.kth.se
(Magnus Pettersson) writes:
 
|> .... There is also a description on how to make two independent and 
|> U(0,1)-distributed random numbers into two independent N(0,1)-distributed
|> randomnumbers, with a method called "the Box-Mueller Method". That method is
|> first described in 
|> 
|> 3. G.E.P.Box and M.E.Mueller
|>    A Note on the Generation  of Random Normal Deviates
|>    Ann.Math.Stat. (1958) 29, 610-611

Don't use this method in single precision - it has a very serious
flaw.  While it is OK in double precision, there are faster and simpler
methods available (e.g. the Polar Method as described in Knuth).  The
reference for the flaw is by H.R. Neave round about 1970.


Nick Maclaren
University of Cambridge Computer Laboratory,
New Museums Site, Pembroke Street,
Cambridge CB2 3QG, England.
Email:  nmm@cl.cam.ac.uk
Tel.:   +44 223 334761
Fax:    +44 223 334679
From: lele@violet.berkeley.edu (Sharachchandra Lele;100 BldgT-4;26886;5106440692;NT23)
Newsgroups: sci.math.stat
Subject: Bug in CSS: Statistica program?
Date: 30 Jul 1992 05:40:48 GMT
Organization: University of California, Berkeley
NNTP-Posting-Host: violet.berkeley.edu
Summary: Standard error calculation is "wrong"

While reviewing CSS:Statistica (for DOS) (a summary of which I posted
recently) I found the following "Bug" that I would like to crosscheck
with others who have used this program:

CSS uses the "sample std. dev." formula for calculating standard
deviation. However, when it calculates standard errors (either in the
ANOVA-descriptive stats command, or in GRAPHICS:box/whisker plot), it
appears to use the "population s.d." value! I noticed this when I was
cross-checking the results using SYSTAT.

As far as I know, the convention is to use sample s.d. always.
Have others noticed this bug? Or am I making a mistake? or is there
nothing wrong with this method?

--Sharad Lele
Energy & Resource Group
Univerity of California, Berkeley

Electronic-mail:	lele@violet.berkeley.edu	(Internet)
From: jeff@kuhub.cc.ukans.edu (Jeff Bangert)
Newsgroups: sci.math.stat
Subject: Re: XLispStat - available for MSDOS?
Date: 28 Jul 92 07:27:29 CDT
Organization: University of Kansas Academic Computing Services

In article <1992Jul21.061217.41771@kuhub.cc.ukans.edu>, jeff@kuhub.cc.ukans.edu (Jeff Bangert) writes:
> Is there a version of XLispStat for MSDOS?

Thanks to several people who replied telling me about the Windows
version.  Unfortunately, I've got two 386SX-16's and I don't like to
run Windows.

Thanks to Luke Tierney who said that there was no DOS version and
suggested the Windows version.

[small flame--networking is wierd sometimes!]

The DOS version is at

    umnstat.stat.umn.edu
    /pub/xlispstat/msdos/XLSZIP.EXE

Thanks to my friend Wes who showed me Tierney's book, which lists the
umnstat address. I've been running XLS for a week, not doing anything
much, but it seems to work.

I've been looking for a public domain stat program for DOS for several
years.  All that I've found up to now seem to have problems.
XLISPSTAT is exactly what I wanted.

Thanks(really) to the person who implemented XLS for DOS.

-- 
Jeff Bangert			jeff@kuhub.cc.ukans.edu
Computer Center			jeff@ukanvax.bitnet
University of Kansas
Lawrence, KS 66045
(913)864-0466
From: jackson@zoo.toronto.edu (Donald Jackson)
Newsgroups: sci.math.stat
Subject: Logistic Regression Program
Date: 27 Jul 92 14:17:23 GMT
Organization: U of Toronto Zoology

I am trying to track down a routine for calculating logistic
regression based on a maximum likelihood approach.  I'd appreciate it
if anyone could point to a source, preferably in FORTRAN.

thanks
-- 
=========================================================================
Donald A. Jackson, Department of Zoology, University of Toronto,
		Toronto, ONT., CANADA, M5S 1A1   (416) 978-3504
INTERNET: jackson@zoo.utoronto.ca
From: edwill@ariel.lerc.nasa.gov (Glenn L. Williams)
Newsgroups: sci.math
Subject: Information on new proof techniques
Date: 23 Jul 92 18:10:00 GMT
Organization: NASA Lewis Research Center
News-Software: VAX/VMS VNEWS 1.41

I recently read (about 6 weeks ago) of a new technique which
tests a mathematical proof for validity.  I.e. it checks that
the proof is correctly done, not that the theorem is proven.
This was touted as using some new abstract reasoning method,
perhaps on a computer, to check the "flow" and syntax in the
proof. It was also touted as being good for checking ALL proofs,
even the old or ancient ones, for validity.

Does anyone know of published papers on this method? If so,
can the references be itemized?
Newsgroups: sci.math