HDTenEightyP/NetNews huggingface dataset:
From: charlie@ernie.stat.washington.edu (Charlie Geyer)
Newsgroups: sci.math.stat
Subject: Re: random number generator
Date: 30 Jul 92 02:05:15 GMT
Organization: Univ of Wash , Stat Dept.

In article <1992Jul29.092934.23335@cl.cam.ac.uk>, nmm@cl.cam.ac.uk
(Nick Maclaren) writes:

> It's not making it a FAQ that's the problem - it's finding a GAA (Generally
> Agreed Answer)!

In article <1992Jul29.090353.237@nutmeg.hnrc.tufts.edu> jerry@nutmeg.hnrc.tufts.edu (Jerry Dallal) writes:

> I suspect one of the most FAQs is what generator to use.  Can we not establish
> a short list of GAAs?  I nominate the Wichmann-Hill generator with the
> McLeod modification.  (I hold off on posting the code until I hear whether 
> this is a GAA!)

I nominate Marsaglia's "Super-Duper" generator, though it's 20 years old
and not the one Marsaglia is using now.

Reason: it's the one S uses so if it's garbage there have been a lot of
garbage simulations done including some of mine.  Don't tell me that's
not a theorem, I already know.


-- 
Charles Geyer
School of Statistics
University of Minnesota
charlie@umnstat.stat.umn.edu
Newsgroups: sci.math.stat
From: Jim.Buddenhagen@bbs.oit.unc.edu (Jim Buddenhagen)
Subject: random number generator
Keywords: pseudo-random, C , uniform, normal
Organization: Southwestern Bell Telephone Company
Date: Sat, 25 Jul 1992 19:16:38 GMT

(apologies if you see this twice --  I posted from another machine but
 it didn't seem to make it to the network)

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
(previous line email preferred)
314-235-5183                One Bell Center, Room 27-X-5
                            St. Louis, MO 63130
--
   The opinions expressed are not necessarily those of the University of
     North Carolina at Chapel Hill, the Campus Office for Information
        Technology, or the Experimental Bulletin Board Service.
           internet:  bbs.oit.unc.edu or 152.2.22.80
Newsgroups: sci.math.stat
From: gibsoni@ee470.ee.mcgill.ca ( irwin roger  gibson)
Subject: Nonlinear Regression Analysis software
Organization: EE Lab, McGill University EE Lab, Montreal
Date: Fri, 24 Jul 92 16:09:36 GMT

		NON-LINEAR REGRESSION ANALYSIS SOFTWARE
		=======================================

If anyone has or knows of any DOS or UNIX nonliner regression analysis
software packages please contact me.  It would be perfered if the software
was available via ftp or email.


This software is urgently required for use in Neural Network Research.


"I thank you for your cooperation and time."
********************************************
gibsoni@ee470.ee.mcgill.ca

Irwin Gibson
D'Ombrain Computer Facility
Dept. of Electrical Engineering
McGill University
Montreal, Quebec CANADA
H3A 2K6

Newsgroups: sci.math.stat
From: grchang@athena.mit.edu (Saihsueh G Chang)
Subject: C program for time-series modeling
Keywords: time-series, forecasting, prediction
Organization: Massachusetts Institute of Technology
Date: Wed, 29 Jul 1992 19:08:34 GMT

Hi,

Does anyone know where I can get the source code of a C program for time-series
modeling?  I am interested in forecasting subroutines (e.g. AR, ARMA, ARIMA,
Box-Jenkins ...).  Thanks a lot.

Please email to:

	grchang@athena.mit.edu

-- Grace Chang
Newsgroups: sci.math.stat
From: thisted@galton.uchicago.edu (Ronald A. Thisted)
Subject: Re: random number generator
Keywords: pseudo-random, C , uniform, normal
Organization: Dept of Statistics, Univ of Chicago
Date: Mon, 27 Jul 1992 15:28:41 GMT

In article <1992Jul27.103659.11820@kth.se> md87-mpe@hemul.nada.kth.se (Magnus Pettersson) writes:
 [regarding a reference to a classic (and somewhat dangerous)
 algorithm for generating gaussian random variates]

>3. G.E.P.Box and M.E.Mueller

For everyone's information, that's Mervin Muller -- no e, no umlaut.

Ron Thisted
Department of Statistics/The University of Chicago
thisted@galton.uchicago.edu
Newsgroups: sci.math.stat
From: Risto Virtanen <rvirta@polaris.utu.fi>
Subject: Re: SAS/Probit for mac?
Organization: Turku School of Economics
X-Useragent: Nuntius v1.1
Date: Sat, 25 Jul 92 18:35:16 GMT

In article <5388@lhdsy1.lahabra.chevron.com> Martin J. Hillyer,
hillyer@rrc.chevron.com writes:
>SAS has a product out for the Mac - it's called JMP (tm).  It will do
probit 
>analysis, I think.
JMP has logistic regression (selected automatically if dep var is nominal
or ordinal). 
Nonlinear Regression has Probit Model with Binomial Errors among others, 
p. 447 in the manual...
I haven't used it though.
Hope this helps
Roisto
From: hillyer@rrc.chevron.com (Martin J. Hillyer)
Newsgroups: sci.math.stat
Subject: Re: SAS/Probit for mac?
Date: 23 Jul 92 20:50:43 GMT
Reply-To: hillyer@rrc.chevron.com
Organization: Chevron, Richmond, California

In article 1@ulys.unil.ch, hsaiah@ulys.unil.ch () writes:
>hello,
>I want to know if a version af SAS (or just the Probit part) exist for
>Macintosh. is it existing other mac program doingthe same analysis as
>Probit in SAS? any informations are welcome. 
>thanks  bye
>
>SAIAH henni,Institute of Zoology, Lausanne University (Switzerland)
>      Email: Hsaiah@ulys.unil.ch

SAS has a product out for the Mac - it's called JMP (tm).  It will do probit analysis, I think.

Martin.



Newsgroups: sci.math.stat
From: duncan@loris.cisab.indiana.edu (Shan Duncan)
Subject: "trends" and others
Organization: Indiana University
X-Newsreader: Tin 1.1 PL4
Date: Tue, 21 Jul 92 16:48:31 GMT


I would like to know how people feel about using such words as "trend".


For example:

When I see the statement:

   The data demonstrates a trend towards [fill in the blank], but this
   relationship was not significant.

Technically this is correct.   In other words I have been told by someone
that you can state a direction (i.e. less, more, greater whatever) as a trend
as long as you state if it is significant or not.  Yet at times I read this
as being "hopeful".  I have seen this type of statement used when  the person
writing the article wants to have the trend in that direction, but they did
not achive statistical significance.  

I have also seen statements such as:  There was a greater response to
[again fill in the blank] but this was not significant.

I am more comfortable with the former rather than the latter.


So what are the rules of thumb in cases such as these?


Newsgroups: sci.math.stat
From: thisted@galton.uchicago.edu (Ronald A. Thisted)
Subject: Re: random number generator
Organization: Dept of Statistics, Univ of Chicago
Date: Mon, 27 Jul 1992 18:15:20 GMT

In article <1992Jul27.132508.217@ginger.hnrc.tufts.edu> jerry@ginger.hnrc.tufts.edu (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:
>>  
 [regarding the Box-Muller method of generating normal deviates]
>> 
>> 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.

>...There is nothing wrong with the Box-Muller method.  It is
>theoretically sound... [description of method and other comments
>omitted]

>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.  

Well, actually, the problem is an *interaction* between multiplicative
linear congruential uniform random number generators (modulo 2^^k) and
the Box-Muller transformation.  The Neave interaction occurs with all
such uniform generators, but the problem is most pronounced when the
multiplier is small relative to the modulus.  However, this is a
*sufficient* but not necessary condition for the problem to occur, a
fact ignored in the followups to Neave's paper.  As a simple example,
if  a  is a "bad" multiplier, exactly the same problem will occur if
the random number stream is "played in reverse order", that is, if the
multiplier is replaced by  a^{-1} mod m, where  m  is the modulus of
the generator.  But a^{-1} can be quite large relative to  m, and is
generally not easy to compute (without Macsyma or Maple or
Mathematica).  And, as Nick Maclaren points out, the Marsaglia
modification -- based on exactly the same theorem -- is usually
faster, cheaper, and as easy to program.

This is an example of a rare phenomenon that I am particularly
interested in, namely, the situation where two natural algorithms,
each of which is at least adequate, can fail miserably in some way
when combined.

Ron Thisted
Department of Statistics/The University of Chicago
thisted@galton.uchicago.edu
Newsgroups: sci.math.stat
From: mk9y@faraday.clas.Virginia.EDU (Michael  Kubovy)
Subject: Regression and bootstrap query
Organization: University of Virginia
Date: Fri, 24 Jul 1992 09:23:53 GMT

I have a designed experiment in which each of 50 subjects responds to
a figure in each of 180 orientations. For each subject I perform a
robust linear regression of the subject's reaction time, rt
(to a property of that figure) on the figure's orientation.
I have one rt per orientation.

I would like to use bootstrapping to estimate the s.e. of the slope
and the intercept of each subject.

Because the regressor is not subject to
error, I must use fixed resampling. But I can't resample the residuals
this way because I have only one residual for each level of the i.v.

Any advice?
--
|\  /| / MICHAEL KUBOVY (kubovy@virginia.edu)
| \/ |/		OFFICE: 804-982-4729; LAB: 982-4751; FAX: 982-4766
|    |\ 	   Department of Psychology, Gilmer Hall,
|    | \ 	   Univ. of Virginia, Charlottesville, VA 22903-2477
Newsgroups: sci.math.stat
From: delz3530@csd4.csd.uwm.edu (Andrew J.G. Delzer)
Subject: StatGraphics Conversion Needed
Originator: delz3530@csd4.csd.uwm.edu
Organization: University of Wisconsin - Milwaukee
Distribution: na
Date: Tue, 28 Jul 1992 16:05:45 GMT


	A coleague of mine has some staticial data that he entered into
  StatGraphics while at the University of Tennessee-Knoxville.  Here at the
  University of Wisconsin-Milwaukee we use MiniTab and are unable to convert
  his StatGraphics data (all files ending in *.ASF) to ASCII for inputing into
  Minitab.
	If someone with access to StatGraphics would be willing to convert
  his data to ASCII, he would be very appreiciative.  The data consists of 
  5 small files, and I could EMail them to you.

	Thank you very much

	Andrew J.G. Delzer and Richard Gagliano
	delz3530@csd4.csd.uwm.edu

Xref: sparky sci.math.stat:1568 comp.ai.neural-nets:3027
From: batra@boulder.Colorado.EDU (sajeev batra)
Newsgroups: sci.math.stat,comp.ai.neural-nets
Subject: question on scoring prediction accuracy of a classifier
Date: 31 Jul 92 05:27:11 GMT
Organization: University of Colorado, Boulder




Suppose I have a classifier that classifies objects into one of n 
classes (populations).  I train the classifier with a "train set."  And to 
test the prediction accuracy of the classifier I predict on a "predict set."
I am wondering: what are some of the better ways to score the
prediction accuracy of my classifier?  All classifications & 
misclassifications have equal cost. 

Here the ways that I'm aware of:

1) (c1 + c2 + ... + cn)/total no. of predictions made
   where cn is the no. of correct predictions made in class n


2) sample correlation coefficient which gives the correlation between
   the prediction and the actual.  the coefficient is always between
   -1 and +1.  There will be a coefficient for each class.  this
   coefficient takes into account type 1 and type 2 errors.


What other popular ways are there to score the prediction accuracy???  
I think I saw someone using the mutual information fuction between the 
predicted and the actual to score the prediction accuracy.  Would this work? 

I would like to know other ways and some of the problems associated with 
them, including the ones I've listed above.  Also, I'm not sure when I can 
assume a certain distribution in my n populations (for example, a normal 
dist.)?          

---sb

 
Newsgroups: sci.math.stat
From: dj@cfa.harvard.edu (Diab Jerius)
Newsgroups: sci.math.stat
Subject: more random number generator questions...
Summary: ranlib STATLIB random numbers
Date: 29 Jul 92 18:12:26 GMT
Organization: Smithsonian Astrophysical Observatory, Cambridge, MA,  USA


yet another RNG question:
can anyone comment upon the robustness of the `ranlib' package distributed
via STATLIB?  in particular it generates gaussian deviates according
to:
               Ahrens, J.H. and Dieter, U.                              
               Extensions of Forsythe's Method for Random               
               Sampling from the Normal Distribution.                   
               Math. Comput., 27,124 (Oct. 1973), 927 - 937.            

thanks in advance.
-- 
diab jerius                                     harvard-smithsonian 
internet: jerius@cfa.harvard.edu              center for astrophysics  
voice: (617) 496-7575               60 garden st., m/s 81 cambridge, ma 02138
From: ajayshah@almaak.usc.edu (Ajay Shah)
Newsgroups: sci.math.stat
Subject: C source for Park-Miller "minimal std. generator":
Date: 25 Jul 1992 14:05:23 -0700
Organization: University of Southern California, Los Angeles, CA
NNTP-Posting-Host: almaak.usc.edu
Keywords: pseudo-random, C , uniform, normal

#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. */

static long int seed = 1;
/* static so programs will be more "orderly" in modifying the
   seed.  The setseed function is the prescribed way in which the seed
   is altered.  A good default to use is your SSN.
   Any seed from 1 to 2147483646 is equally ok. */

int setseed(long int newseed)
{
    if ((newseed < 1) || (newseed > 2147483646)) return 1;
    seed = newseed; return 0;
}

double ranpm()
     /* page 1195-right, "Integer Version 2", works iff ints are 32 bits.*/
{
    long int a=16807, m=2147483647, q=127773, r=2836;
    int lo, hi, test;

    hi = seed / q;
    lo = seed % q;
    test = a * lo - r * hi;
    seed = (test > 0) ? test : test + m;
    return (seed/ (double) m);
}

#ifdef TESTING
/* They give us one test (on page 1195-left): if seed = 1 then
   the 10001'th random number should be 1043618065.
   Apart from this, I do some superficial testing aimed at checking
   the code above is not buggy.  I'm not trying to test the
   statistical properties of the RNG. */

int main()
{
    int n; double u, sum=0.0, sum2=0.0;
    
    for (n=1; n<=10000; n++) {
	u = ranpm();
	if ((u < 0.0) || (u > 1.0)) {
	    printf("Garbage at the %dth number!\n");
	    return 1;
	}
	sum += u;
	sum2 += (u*u);
    }
    printf("The current value of seed is : %10d\n", seed);
    printf("The Truth is %17s 1043618065\n\n", " ");

    printf("Mean of 1st 10k nums is %f, variance is %f\n",
	   sum/10000, sum2/9999);
    printf("Expect .5018 and .3355\n");
    return 0;
}
#endif /* TESTING */
-- 
Ajay Shah, (213)749-8133, ajayshah@usc.edu
Newsgroups: sci.math.stat
From: engelson-sean@CS.YALE.EDU (Sean Philip Engelson)
Subject: Correlation test (sort of)?
Organization: Yale AI Mobile Robotics Project
Date: Fri, 31 Jul 1992 13:58:44 GMT


Please forgive my statistically untutored way of speaking, but I have what I
think should be a relatively simple hypothesis testing problem, which I (not
being a statistician) don't quite know how to approach.

There is a process (unmodelable) which I can measure in two different ways,
giving me values, call them X and Y, for different states of the underlying
process.  I would like to make statements of the form: 

  When X is high, Y is (usually) low.  ("high" and "low" can be interchanged)
	(note the asymmetry, if X is low, we don't care about Y)

I need a statistical testing method that gives me a measure of my confidence in
such a statement.  If necessary, I can put in threshholds defining "high" and
"low", but I'd prefer not to (or to get them out of the method).  I have a
reasonable number of data points (about 300).  Doing a regression analysis
seems inappropriate, since (a) different values of X can be fundamentally (ie,
ignoring noise) associated with the same value of Y and v.v.  (since the
underlying process state in multidimensional) and (b) the choice of regression
model is not clear (since I have no real model for the process).  Any and all
suggestions would be most helpful, especially references.

Thanks very much.
-- 
Sean Philip (Shlomo) Engelson		Im eshkachekh Yerushalayim, 
Yale Department of Computer Science		Tishkach yemini;  
Box 2158 Yale Station			Tidbak leshoni l.chiki
New Haven, CT 06520				Im lo ezkerekhi...
Newsgroups: sci.math.stat
From: Andrew.Robinson@anu.edu.au
Subject: JMP
Organization: Australian National University
Date: Wed, 29 Jul 92 03:36:50 GMT

We are interested in any information that anyone can offer about JMP for the
mac.  

regardless,
Andrew

now hit d
Newsgroups: sci.math.stat
From: mcclella@yertle.Colorado.EDU (Gary McClelland)
Subject: Names for Bivariate Central Moments? (SUMMARY)
Keywords: bivariate distributions, skew, kurtosis, central moments
Organization: University of Colorado, Boulder
Date: Wed, 29 Jul 1992 15:44:11 GMT

I earlier posted a message asking for help in finding names and/or
intuitive explanations for various central moments of bivariate
distributions.  In particular, what do mu(2,2), mu(2,1), and mu(1,2) tell
us about the bivariate distribution of X and Z, where 
mu(i,j) = E[(X-Xmean)^i (Z-Zmean)^j]?  The following is a summary of
useful responses I received to this question.

Ewart Shaw (strgh@uk.ac.warwick.cu) and Charles Berry
(cberry@tajo.ucsd.edu) independently suggested considering a contour
plot of the bivariate distribution.  Then, in Shaw's words,

>You could call mu(2,1), mu(1,2) & mu(2,2) `U-ness', `C-ness' & `X-ness'
>(positive values suggest that, `other things being equal', the contour
>plots of the distns. will have these shapes).

This suggestion was especially useful to me because in my problem
m(2,2) has a central role and it is clear in this problem why "X-ness"
would be important.

Terry Moore (T.Moore@massey.ac.nz) suggested:

>Look into Mardia's bivariate skewness and kurtosis. They use 
>mu(2,1), mu(1,2), and mu(2,2). You should be able to find these in
>the Encyclopaedia of Statistical Sciences.

Following this lead I found Mardia's 1970 Biometrika (Vol 57, 519-530)
paper to be very useful.  When X and Z are uncorrelated and have unit
variances, he shows that his definitions of bivariate skewness and
kurtosis reduce to:

bivariate skew = mu(3,0)^2 + mu(0,3)^2 + 3mu(1,2)^2 + 3mu(2,1)^2

bivariate kurtosis = mu(0,4) + mu(4,0) + 2mu(2,2)

I am most grateful for these useful suggestions for understanding
bivariate central moments.  Once again, I'm amazed by the power of the
electronic community.  If anyone has any further suggestions, I would
be eager to hear about them.

gary mcclelland
univ of colorado
mcclella@yertle.colorado.edu

Newsgroups: sci.math.stat
From: wwj@wwj.arc.nasa.gov (Walter Johnson)
Subject: Connection Test
Organization: NASA Ames Research Center
Date: Tue, 21 Jul 1992 23:12:02 GMT

	This is just a test (again)!
Please ignore.
From: jerry@ginger.hnrc.tufts.edu (Jerry Dallal)
Newsgroups: sci.math.stat
Subject: Re: random number generatorDIR
Date: 30 Jul 92 14:29:16 GMT
Organization: USDA HNRC at Tufts University

In article <1992Jul30.020515.16652@u.washington.edu>, charlie@ernie.stat.washington.edu (Charlie Geyer) writes:
> In article <1992Jul29.090353.237@nutmeg.hnrc.tufts.edu> jerry@nutmeg.hnrc.tufts.edu (Jerry Dallal) writes:
> 
>> I suspect one of the most FAQs is what generator to use.  Can we not establish
>> a short list of GAAs?  I nominate the Wichmann-Hill generator with the
>> McLeod modification.  (I hold off on posting the code until I hear whether 
>> this is a GAA!)
> 
> I nominate Marsaglia's "Super-Duper" generator, though it's 20 years old
> and not the one Marsaglia is using now.
> 

SUPER-DUPER would have been my second choice.  What is Marsaglia using now, and
why is it not SUPER-DUPER?
Newsgroups: sci.math.stat
From: nmm@cl.cam.ac.uk (Nick Maclaren)
Newsgroups: sci.math.stat
Subject: Re: random number generator
Keywords: pseudo-random, C , uniform, normal
Date: 29 Jul 92 09:29:34 GMT
Reply-To: nmm@cl.cam.ac.uk (Nick Maclaren)
Organization: U of Cambridge Computer Lab, UK

In article <1126@kepler1.rentec.com>, andrew@rentec.com (Andrew
Mullhaupt) writes:
 
|> Why don't we make RNG a FAQ for sci.math.stat?

It's not making it a FAQ that's the problem - it's finding a GAA (Generally
Agreed Answer)!

Some of my recent replies are based on work that has been published in 1992,
and I frequently hear from other workers about important results that I had
missed (often in the most bizarre journals).  The area may not be large, but
it is awfully confused.


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
Newsgroups: sci.math.stat
From: ALEWAND@ibm.gwdg.de
Subject: Stochastically larger??
Organization: GWDG, Goettingen
Date: Wed, 29 Jul 92 11:10:30 MSZ

Let X1,...,Xn and Y1,...,Ym be independent distributed chi-squared
variables with one degree of freedom.
Define
    SX:=a1 *X1 + a2*X2 +... an*Xn        ai>0, i=1,...n
and
    SY:=b1 *Y1 + b2*Y2 +... bm*Ym        bj>0, j=1,...,m.
 
I need sufficient conditions  for  the ai's and the bj's
to show that SX is stochastically larger than SY.
 
Any references, comments and results for special cases would help me!!
 
 
Achim Lewandowski
Institut fuer Statistik und Oekonometrie
3400 Goettingen
Germany
email: alewand@ibm.gwdg.de
From: jeff@kuhub.cc.ukans.edu (Jeff Bangert)
Newsgroups: sci.math.stat
Subject: XLispStat - available for MSDOS?
Date: 21 Jul 92 11:12:17 GMT
Article-I.D.: kuhub.1992Jul21.061217.41771
Organization: University of Kansas Academic Computing Services

Is there a version of XLispStat for MSDOS?

Thanks,

-- 
Jeff Bangert			jeff@kuhub.cc.ukans.edu
Computer Center			jeff@ukanvax.bitnet
University of Kansas
Lawrence, KS 66045
(913)864-0466
Newsgroups: sci.math.stat
From: gibsoni@ee470.ee.mcgill.ca ( irwin roger  gibson)
Subject: Bayes Classifier & Cluster Analysis software required
Organization: EE Lab, McGill University EE Lab, Montreal
Date: Fri, 24 Jul 92 16:01:20 GMT

Bayesian Classifier & Cluster Analysis
=======================================

If anyone has or knows of the following types of software and there
availability: (ftp or email)

Bayesian Classifier & Cluster Analysis (DOS or UNIX)

This software is urgently required for use in Neural Network Research.


"I thank you for your cooperation and time."
********************************************
gibsoni@ee470.ee.mcgill.ca

Irwin Gibson
D'Ombrain Computer Facility
Dept. of Electrical Engineering
McGill University
Montreal, Quebec CANADA
H3A 2K6