From chemistry-request@server.ccl.net Sun Dec  1 20:02:27 2002
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Date: Mon, 2 Dec 2002 9:2:13 +0800
From: "Liu zhiguo" <zgliu@sohu.com>
Reply-To: zgliu@sohu.com
To: "CHEMISTRY@ccl.net" <CHEMISTRY@ccl.net>
Subject: Gromacs vs Amber
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Dear CCLers,
  I'm going to do some work relating to MD.As far as I know,The most commonly used softwares of MD is Gromacs and Amber.I wonder which one is better for me(My research object is nuclear receptor).Could someone make a comparision between them?

	


Best regards!
          _______________________________________
         |                                       |
         |  Liu zhi-guo,Ph.D candidate,          |
         |  Shanghai Institute of Materia Medica`|
         |  Phone:021-64311833-615               |
         |  Email:zgliu@sohu.com                 |
         |_______________________________________|





From chemistry-request@server.ccl.net Mon Dec  2 03:53:53 2002
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Date: Mon, 2 Dec 2002 03:53:48 -0500 (EST)
From: Yong Liang Yang <yonyang@ic.sunysb.edu>
To: chemistry@ccl.net
Subject: Convergence failure in geometry optimization of big molecule
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hello,dear CCL mates:

I am still trying to do the geometry optimization stuff
for a big molecule containing boron and nitrogen. The solvation
model I was chosing is PCM and I have set the radius of the negative
charge center nitrogen using NSFE option with Dump. To increase the
tesserae number, TSNUM option is used. After four days CPU time,
the job is terminated due to convergence failure, (Convergence criterion
not met). And the hint given is: Hint: increase the number of tesserae or
change the molecule orientation. But actually I have inceased the tesserae
number and I am not sure what is the deal to change the molecule
orientation. Does anyone who have some suggestions on the SCF convergency
of a big system in solvation model? Thank you all in advances.

Yongliang Yang

regards




From chemistry-request@server.ccl.net Mon Dec  2 07:33:06 2002
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Dear all,

has anyone out there experience with the EFP modules in GAMESS?
I'd really like an example-input made from a runtyp=makefp to get the 
syntax right. I also wonder if there's a way to make a fragment with 
less than 3 atoms - and if so - how does one fill in the xyz coordinates 
in the $efrag?

sincerely

/Patrik
-- 
Dr. Patrik Johansson, Materials Physics Group, Chalmers, Sweden.


From chemistry-request@server.ccl.net Mon Dec  2 10:07:29 2002
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Dear CCL,

I have attached a log file that I generated whilst attempting to compile
GAMESS (May 1997 version) using forte v7 fortran compiler and the CC C
compiler on a SUN.

The code appears to be incorrect. Do you know if later versions of
GAMESS have remedied this problem?

Is their an email address at Ames that I could contact about this issue?

Richard Greaves.

From chemistry-request@server.ccl.net Mon Dec  2 11:57:19 2002
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From: Dmitry Kovalsky <dikov@imbg.org.ua>
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Subject: Cartesian vs DLC
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Dear CCL,

While performing structure optimization of the enzyme's active site (two 
identical chains each of 4 residues interconnected by 4 h-bonds) with bound 
Na+ ion to it,  I have noted that the choice of coordinates (CART or DLC) to 
be used dramatically infulences the final geometry. 

In case of DLC coordinates the distance between these two chains increses in 
few Angstroms while Na+ almost immobile. In contrast when the Cartesians is 
used the Na+ moves a lot and the active site moves very little.

Is it Ok? 
What result should I believe?  

Sincerely yours,

Ph.D. Student Dmitry Kovalsky
Institute of Molecular Biology & Genetics
150 Akad. Zabolotnogo Street,
Kiev-143, 03143
UKRAINE

E-mail: dikov@imbg.org.ua
Fax:  +380 (44) 266-0759
Tel.: +380 (44) 266-5589



From chemistry-request@server.ccl.net Mon Dec  2 01:50:31 2002
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Date: Mon, 02 Dec 2002 07:49:50 +0100
From: "Dr. Andreas Klamt" <andreas.klamt@cosmologic.de>
Organization: COSMOlogic GmbH&CoKG
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To: Parthiban <parthi.s@jubilantbiosys.com>,
   "chemistry@ccl.net" <chemistry@ccl.net>
Subject: Re: CCL:Quantum Chemistry in Drug Design
References: <20021130014134.M78797@jubilantbiosys.com>
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My view of this topic is as follows: I am afraid, that realistic modeling of drug receptor interaction is still too demanding
for quantum chemical methods, because  usually the enzyme is too large, and in addition a lot of conformations and many
compounds would have to be sampled. 

The situation is different if you consider the ADME part: Here we can do good calculations of solubility and many kinds of
physiological partitioning properties quite efficiently using DFT methods. The advantage compared with force field models is
that you can get much better insight into the real physics using quantum chemistry. For examples see:

http://www.cosmologic.de/water_solubility.html

or
"COSMO-RS: a novel view to physiological solvation and partition questions", Andreas Klamt, Frank Eckert and Martin Hornig,
 Journal of Computer-Aided Molecular Design 15, 355-365 (2001)
and
"Prediction of aqueous solubility of drugs and pesticides with COSMO-RS", Andreas Klamt, Frank Eckert, Martin Hornig, Michael E.
Beck and Thorsten Bürger, J. Comp. Chem. 23, 275-281 (2002)


Andreas

Parthiban schrieb:
> 
> Dear Friends:
> While several QSAR related techniques and methodologies are appearing in drug
> design Journals, very few talk about the more accurate quantum chemical
> methods in drug design arena.
> 
> * What are the bottlenecks for the quantum chemical methods to get into the
> area of drug design.
> 
> * For small molecules QC methods plays greater role, but for handling drug-
> like molecules and handling several thousands of compounds, QC methods do not
> see the limelight (correct me if i am wrong). Is the CPU-intensiveness alone
> is the reason. Or is there any some conceptual gap in this. [ I hear someone
> saying CPU-intensive is the reason and one has to wait for months to get
> results ]
> 
> * Based on your experience/insight, can you think of some timeframe, say 5
> years, 10 years down the line, Quantum chemical methods would play a major
> role in the area of lead identification/optimization, or would you
> say "prediction of future is difficult!".
> 
> I look forward to reading your views. Thanks.
> 
> S. Parthiban
> Jubilant Biosys Ltd.
> http://www.jubilantbiosys.com
> 
> -= This is automatically added to each message by mailing script =-
> CHEMISTRY@ccl.net -- To Everybody  | CHEMISTRY-REQUEST@ccl.net -- To Admins
> Ftp: ftp.ccl.net  |  WWW: http://www.ccl.net/chemistry/   | Jan: jkl@ccl.net

-- 
--------------------------------------------------------------------------------
Dr. Andreas Klamt
COSMOlogic GmbH&CoKG
Burscheider Str. 515
51381 Leverkusen, Germany

Tel.: 49-2171-73168-1  Fax: ...-9
e-mail: andreas.klamt@cosmologic.de
web:    www.cosmologic.de
--------------------------------------------------------------------------------
COSMOlogic
        Your Competent Partner for
        Computational Chemistry and Fluid Thermodynamics
--------------------------------------------------------------------------------



From chemistry-request@server.ccl.net Mon Dec  2 11:20:19 2002
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I am calculating the hyperfine tensor by using the prop=EPR keyword in 
Gaussian 98 (A.9). I want to add ghost atoms (Bq) to the molecule and 
calculate the hyperfine tensor at those sites. The output of EPR only gives 
values for the atoms in the molecule and not the ghost atoms. In Gaussian 
94, using prop=EFG IOp(6/17=2,6/26=4), which is equivalent to EPR, gives 
the hyperfine tensor for both atoms and ghost atoms. Is there any way to 
get the hyperfine tensor for ghost atoms in G98 (prop=EFG 
IOp(6/17=2,6/26=4) gives the same results as prop=EPR )?
  -- Milo

===============================================================================
                 National Magnetic Resonance Facility at Madison,
                         An NIH-Supported Resource Center
W. Milo Westler, Ph.D.                          EMAIL: milo@nmrfam.wisc.edu
NMRFAM Director                                 PHONE: 
(608)-263-9599
                                                 FAX:   (608)-263-1722
Senior Scientist
       and
Adjunct Professor
433 Babcock Drive
Department of Biochemistry
University of Wisconsin-Madison
Madison, WI USA 53706-1544
===============================================================================



From chemistry-request@server.ccl.net Mon Dec  2 12:45:27 2002
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From: "Robert Q. Topper" <topper@cooper.edu>
To: CHEMISTRY@ccl.net
Cc: TOPPER ROBERT <topper@cooper.edu>
Subject: ECCC9: Abstracts Due Friday December 13, 2002
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ECCC9: Abstracts Due Friday December 13, 2002

Dear colleagues, 

We are pleased to announce that abstracts are being accepted to the 9th 
Electronic Computational Chemistry Conference. All abstracts must be 
submitted on or before Friday, December 13.

ECCC9 will be held March 1 - March 31, 2003 entirely on the Internet, at 
http://eccc9.cooper.edu. Abstracts are now being accepted for online 
submission at the conference website.

As in previous years, ECCC9 is a multidisciplinary international 
conference and covers all aspects of computational and theoretical 
chemistry, chemical physics and materials science, as well as 
computational molecular biology, computational and theoretical molecular 
and atomic physics, visualization, cheminformatics, the history of 
computational chemistry, and related fields. 

Participants will be able to view the presentations and discuss them 
entirely through a web browser. As with the previous eight ECCCs, ECCC9 
has NO registration fee and is a completely virtual, online conference 

Abstracts for all contributions to ECCC9 will be reviewed by the 
Scientific Organizing Committee (SOC) to insure novelty, scientific 
value, and appropriateness for inclusion in the conference. All ECCC9 
presentations must be in HTML format, with their layout and presentation 
at the discretion of the authors. 

Important dates for ECCC9 are: 

December 13, 2002 - Abstracts of presentations due 
February 24, 2003 - Final presentations due online 

March 1, 2003 - Conference begins 
March 17, 2003 - Interactive Session begins 
March 24, 2003 - Interactive Session ends 
April 1, 2003 - ECCC9 ends 

May 1, 2003 - Submissions to ECCC9 - IJMS Proceedings due 

The Proceedings of ECCC9 will be published in a special issue of the 
International Journal of Molecular Sciences (http://www.mdpi.net/ijms/). 
IJMS is a peer-refereed scientific journal, published online monthly 
(since September 2001) and CD-ROM yearly. It is indexed and abstracted by 
several leading indexing and abstracting services, including Chemical 
Abstracts and CAPLUS, and is physically distributed to various libraries 
around the world. IJMS articles are freely available to all on the 
Internet. Please see the ECCC9 RAnnouncementsS page for more information.

We look forward to your participation in ECCC9. 

Robert Q. Topper, Robert Hopkins and Christopher Lent
 
Albert Nerken School of Engineering 
The Cooper Union for the Advancement 
of Science and Art 

51 Astor Place 
New York, NY 10003 
topper@cooper.edu 
http://eccc9.cooper.edu 






From chemistry-request@server.ccl.net Mon Dec  2 13:32:57 2002
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Hello Dimitry and All!

On Mon, 2 Dec 2002, Dmitry Kovalsky wrote:

> Na+ ion to it,  I have noted that the choice of coordinates (CART or DLC) to
> be used dramatically infulences the final geometry.

> Is it Ok?
> What result should I believe?

Usually the one with the lower energy is the better geometry. But when
modelling an enzyme it might not be what you really want. You could try
to do a Cartesian based optimization on the structure optimized with
internal coordinates, and vice versa, and see what happens to the
structure.

As a side note, it's a good idea to specify what program you are using,
it usually makes answering easier :-)

Have a nice day,
    Mikael J.
    http://www.helsinki.fi/~mpjohans/


From chemistry-request@server.ccl.net Mon Dec  2 13:55:09 2002
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Date: Mon, 2 Dec 2002 13:55:05 -0500 (EST)
From: Alfredo Cardenas <alfredo@CS.Cornell.EDU>
To: chemistry@ccl.net
Subject: steepest descent path program
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Hello all,
Does anybody have a code to compute the steepest descent path
between two minima states (coordinates)? Or could you point me to anyone
that could have such a code?
Thanks a lot,

Alfredo Cardenas
Dept. Computer Science
Cornell University
alfredo@cs.cornell.edu 


From chemistry-request@server.ccl.net Mon Dec  2 20:09:06 2002
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To: chemistry@ccl.net
Cc: james.metz@abbott.com
Subject: CCL:constrained multiple linear regression
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CCL,

        I am looking for software (preferably free or inexpensive, code is 
OK) that will allow me to perform
constrained multiple linear regression.  For example, I have an equation 
of the form:

        Y = a*X1 + b*X2 + c*X3 + d

        where: Y is the dependent variable
                  X1 - X3 are independent variables (more than 1)
                a, b, c are coefficients
                        d is a constant

        I must be able to constrain the range of values for a, b, c, and d 
during the fitting.

        Please note that programs such as JMP, KalediaGraph, GraphPad 
Prism, and several other packages do 
NOT allow the user to do this, especially for more than one independent 
variable.

        Can someone suggest a program or code to do this?

        Thank you,
        Jim Metz


James T. Metz, Ph.D.
Research Investigator Chemist

GPRD R46Y AP10-2
Abbott Laboratories
100 Abbott Park Road
Abbott Park, IL  60064-6100
U.S.A.

Office (847) 936 - 0441
FAX    (847) 935 - 0548

james.metz@abbott.com

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<br><font size=2 face="Arial">CCL,</font>
<br>
<br><font size=2 face="Arial">&nbsp; &nbsp; &nbsp; &nbsp; I am looking for software (preferably free or inexpensive, code is OK) that will allow me to perform</font>
<br><font size=2 face="Arial">constrained multiple linear regression. &nbsp;For example, I have an equation of the form:</font>
<br>
<br><font size=2 face="Arial">&nbsp; &nbsp; &nbsp; &nbsp; Y = a*X1 + b*X2 + c*X3 + d</font>
<br>
<br><font size=2 face="Arial">&nbsp; &nbsp; &nbsp; &nbsp; where: Y is the dependent variable</font>
<br><font size=2 face="Arial">&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; X1 - X3 are independent variables (more than 1)</font>
<br><font size=2 face="Arial">&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; a, b, c are coefficients</font>
<br><font size=2 face="Arial">&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; d is a constant</font>
<br>
<br><font size=2 face="Arial">&nbsp; &nbsp; &nbsp; &nbsp; I must be able to constrain the range of values for a, b, c, and d during the fitting.</font>
<br>
<br><font size=2 face="Arial">&nbsp; &nbsp; &nbsp; &nbsp; Please note that programs such as JMP, KalediaGraph, GraphPad Prism, and several other packages do </font>
<br><font size=2 face="Arial">NOT allow the user to do this, especially for more than one independent variable.</font>
<br>
<br><font size=2 face="Arial">&nbsp; &nbsp; &nbsp; &nbsp; Can someone suggest a program or code to do this?</font>
<br>
<br><font size=2 face="Arial">&nbsp; &nbsp; &nbsp; &nbsp; Thank you,</font>
<br><font size=2 face="Arial">&nbsp; &nbsp; &nbsp; &nbsp; Jim Metz</font>
<br><font size=2 face="Arial"><br>
<br>
James T. Metz, Ph.D.<br>
Research Investigator Chemist<br>
<br>
GPRD R46Y AP10-2<br>
Abbott Laboratories<br>
100 Abbott Park Road<br>
Abbott Park, IL &nbsp;60064-6100<br>
U.S.A.<br>
<br>
Office (847) 936 - 0441<br>
FAX &nbsp; &nbsp;(847) 935 - 0548<br>
<br>
james.metz@abbott.com<br>
</font>
--=_alternative 0006511186256C84_=--


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 I'm trying to build the parameters for a MD simulation of an 
epoxidic sistem but a have not found any experimental data of the 
raotational barrier for the dihedral angle H1-C2-C3-C4 in the 
following sistem:

                        _

 I'll be gratefull of any suggestion.

 







 _____________________________________________

 Reynier Suardiaz del Rio
 Department of Physical Chemistry
 Chemistry Faculty
 University of Havana
 email: reynier@fq.uh.cu, reynier_s@yahoo.com
 _____________________________________________


From chemistry-request@server.ccl.net Mon Dec  2 22:20:57 2002
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From: Jan Labanowski <jkl@ccl.net>
To: james.metz@abbott.com
cc: Jan Labanowski <jkl@ccl.net>, chemistry@ccl.net
Subject: Re: CCL:constrained multiple linear regression
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You need a program which does regression through origin (i.e., no
intercept regression. Check references (sorry, it was ages ago when I looked
at it):
     K.W. Smillie - "An introduction to regression and correlation"
        Academic Press, NY 1966 
     S.R. Searle - "Linear models",  J.Wiley & Sons, NY 1971
   
I once write my own routine to do it, but it is in a terribly ancient Fortran
(yes... remember VAXes? in the early 80-ties?).
You have a regression
         Y = X*b + e   
When freeft = 1, then we fit an intercept and the X contains a column of 1's
When freeft = 0, then we have regression throught origin and X does not have
                 a column of 1's

(Note, you can always subtract a constant from all values of Y if you want to
fix intercept at some value. Likewise, if you want to fix some b, you
just subtract the b(j)*X(i,j) from Y(i) )
        Y - column vector of "experimental values"
        X - matrix storing values of independent variables:
            X(i,j) - value j-th independent variable for i-th experimental
        b - column vector of regression coefficients
            b(i) - regresion coefficients corresponding to i-th independent
                   variable
        e - column vector of residuals
        Nexp - number of experimental points
        Nparam - number of fitted regression coefficients

If you have statistical weights, W (i.e., reciprocals of variance for each
experimental point), calculate their mean
    
Wmean = (sum of Wi)/Nexp
and calculate normalized roots of weights as:

Wroot(i) = sqrt(W(i)/Wmean)

Then rescale Y and X by Wroots as:

Y(i) = Y(i) * Wroot(i)    (for i = 1, Nexp)

X(i,j) = X(i,j) * Wroot(i) (for i = 1, Nexp and for j = 1, Nparam)

Then calculate:

C             XTX - on output inverse of X'X matrix (inside the routine,
C                   before inversion, it stores elements of X'X)
C             XTY - X'Y matrix
C             YTY - Y'Y - sum of squares of Yexp(i)
C             rXiXj - array of correlation coefficients between independent
C                   variables Xi and Xj
C             rYXi - array of correlation coefficients between dependent var-
C                  iable Y and independent variable Xi
C             SSE - sum of squares of residuals
C                   SSE = sum of (Yexp(i) - Ytheor(i))**2  (i.e Y'Y - b'X'Y)
C                   both for freeft = 0  &  freeft = 1
C
C             SSR - sum of sqyares about regression
C                   SSR = sum of (Ytheor(i) - Ymean)**2
C                        or b'X'Y - Nexp*Ymean*Ymean  when freeft = 1
C                   SSR = b'X'Y  when freeft = 0
C
C             SST - total sum of squares
C                   SST = (Yexp(i) - Ymean)**2
C                       or Y'Y - Nexp*Ymean*Ymean  when freeft = 1
C                   SST = Y'Y   when  freeft = 0
C
C             MSE - mean square of errors  { MSE = SSE/(Nexp-Nparam)  }
C
C             MSR - mean square of regression
C                   MSR = SSR/Nparam for freeft = 0
C                   MSR = SSR/(Nparam - 1) for freeft = 1
C
C             b   - regression coefficients b = inv(X'X)*X'Y
C                   inv(X'X) is the inverse of X'X 
C
C             seb - standard errors of regression coefficients
C                   seb[i] = SQRT(MSE/inv(X'X[i,i]))
C                          where  inv(X'X[i,i]) is the i,i-element of the
C                                 inverse of X'X matrix 
C
C             seYth - standard errors of regression values
C                     seYth[i] = SQRT(MSE*Xi'*inv(X'X)*Xi) where
C                     Xi is the i-th column of X matrix and
C                     inv(X'X) is the inverse of X'X matrix
C
C             Rmul - multiple regression coefficient that is SQRT(Rmul2) or
C                    in case of Rmul2 < 0 (sometimes in no-intercept model)
C                    Rmul is set to 0
C
C             Rmul2 - Square of multiple correlation coefficient
C                     Rmul2 = SSR/SST
C
C             Xmean - array of means of independent variables
C
C             Ymean - mean of Yexp  (and Ytheor)
C
C             F -  F statistics         F = MSR/MSE
C
C             t - t statistics for each regression coefficient for testing
C                  hypothesis that bstar(i) = 0
C                     t(i) = b[i]/seb[i]
C
C The ugly Fortan follows

       INTEGER*2 Nexp, Nparam, df, i, j, k, l, errflg, mode,freeft
       REAL*8    X(MAXEXP,MAXPAR), Yexp(MAXEXP), Ytheor(MAXEXP),
     1           W(MAXEXP), Wroots(MAXEXP), Wmean, t(MAXPAR),
     2           rXiXj(MAXPAR,MAXPAR), rYXi(MAXPAR), Xmean(MAXPAR),
     3           XTX(MAXPAR,MAXPAR), XTY(MAXPAR), SSE, SSR, SST,
     4           seYth(MAXEXP), seb(MAXPAR), b(MAXPAR), Rmul2,
     5           Rmul, F, MSR, MSE, Ymean, YTY, y, s, s1, s2, aux


C Read in the Yexp, X, W and freeft (find the return statements and
C change them to STOP) or make a subroutine out of this code
C ....................
C

C
C    Calculate Wmean for relative weights
C
       Wmean = 0.0D0
       DO 10 i = 1, Nexp
          Wmean = Wmean + W(i)
10     CONTINUE

       Wmean = Wmean/Nexp
C
C    Rescale Yexp and X for weighted least squares
C

15     DO 20 i = 1, Nexp
          Wroots(i) = SQRT(W(i)/Wmean)
20     CONTINUE

       DO 40 i = 1, Nexp
          s = Wroots(i)
          Yexp(i) = Yexp(i) * s
          DO 30 j = 1, Nparam
             X(i,j) = X(i,j) * s
30        CONTINUE
40     CONTINUE

C
C    Calculate Y'Y and Ymean
C
       YTY = 0.0D0
       Ymean = 0.0D0
       DO 42 i = 1, Nexp
          y = Yexp(i)
          YTY = YTY + y*y
          Ymean = Ymean + y
42     CONTINUE
       Ymean = Ymean/Nexp

C
C    Calculate Xmean
C
       DO 44 i = 1, Nparam
          s = 0.0D0
          DO 43 j = 1, Nexp
             s = s + X(j,i)
43        CONTINUE
          Xmean(i) = s/Nexp
44     CONTINUE


C
C    Calculate X'X
C
       DO 70 i = 1, Nparam
          DO 60 j = i, Nparam
             s = 0.0D0
             DO 50 k = 1, Nexp
                s = s + X(k,i)*X(k,j)
50           CONTINUE
             XTX(i,j) = s
             IF(i .ne. j) XTX(j,i) = s
60        CONTINUE
70     CONTINUE



C
C    Calculate X'Y
C
       DO 90 i = 1, Nparam
          s = 0.0D0
          DO 80 j = 1, Nexp
             s = s + X(j,i) * Yexp(j)
80        CONTINUE
          XTY(i) = s
90     CONTINUE

C
C    Calculate correlation coefficients rXiXj and rYXi
C
       DO 92 i = 1, Nparam
          s1 = Nexp * Xmean(i)**2
          DO 91 j = i, Nparam
             s2 =  Nexp * Xmean(j)**2
             s = XTX(i,j) - Nexp * Xmean(i) * Xmean(j)
             IF (ABS(XTX(i,i) - s1) .LT. 0.00001D0*s1 .OR.
     1           ABS(XTX(j,j) - s2) .LT. 0.00001D0*s2) THEN
                 rXiXj(i,j) = 0.0D0
             ELSE
                 aux = (XTX(i,i)-s1)*(XTX(j,j)-s2)
                 IF(aux .le. 1.0d-30)THEN
                   errflg = 30
                   return
                 end if
                 rXiXj(i,j) = s / SQRT((XTX(i,i)-s1)*(XTX(j,j)-s2))
             ENDIF
             IF(i .NE. j) rXiXj(j,i) = rXiXj(i,j)
91        CONTINUE
92     CONTINUE


       DO 93 i = 1, Nparam
          s = XTY(i) - Nexp * Xmean(i) * Ymean
          s1 = Nexp * Xmean(i)**2
          s2 = Nexp * Ymean*Ymean
          IF (ABS(XTX(i,i) - s1) .LT. 0.00001D0*s1 .OR.
     1        ABS(YTY - s2) .LT. 0.00001D0*s2) THEN
              rYXi(i) = 0.0D0
          ELSE
              aux = (XTX(i,i)-s1)*(YTY-s2)
              if(aux .le. 1.0D-30)THEN
                errflg = 30
                return
              end if
              rYXi(i) = s / SQRT((XTX(i,i)-s1)*(YTY-s2))
          ENDIF
93     CONTINUE


C
C    Invert X'X
C
       CALL syminv(Nparam, XTX, s, errflg)
       IF(errflg .ne. 0)GOTO 999


C
C    Calculate regression coefficients b = inv(X'X)*X'Y
C
       DO 110 i = 1, Nparam
          s = 0.0D0
          DO 100 j = 1, Nparam
             s = s + XTX(i,j) * XTY(j)
100       CONTINUE
          b(i) = s
110    CONTINUE

C
C    Calculate Ytheor (values of y given by regression) Ytheor = X*b
C
       DO 130 i = 1, Nexp
          s = 0.0D0
          DO 120 j = 1, Nparam
             s = s + b(j) * X(i,j)
120       CONTINUE
          Ytheor(i) = s
130    CONTINUE

C
C    Calculate SST
C
       IF(freeft .eq. 1)THEN
          SST = YTY - Nexp*Ymean*Ymean
       ELSE
          SST = YTY
       END IF


C
C    Calculate sum of squares of residuals (SSE)
C
       SSE = YTY
       DO 140 i = 1, Nparam
          SSE = SSE - XTY(i)*b(i)
140    CONTINUE

       IF(SSE .lt. -5.0d-10*YTY)THEN
          errflg = 2
          RETURN
       ELSE IF(SSE .lt. 0.0D0)THEN
         SSE = 0.0D0
       END IF

C
C    Calculate Rmul2,  and SSR (sum of squares due
C    to regression )
C
       df = Nexp - Nparam

       SSR = SST - SSE

       if(abs(SST) .gt. 1.0D-30)then
         Rmul2 = SSR/SST
       else
         Rmul2 = 0.0D0
       end if


C    mean square due to regression (MSR) and mean square of error (MSE)

       IF(freeft .eq. 0)THEN
          MSR = SSR/Nparam
       ELSE
          MSR = SSR/(Nparam - 1)
       END IF


       MSE = SSE/df

C    Calculate F statistic (F), multiple regression coefficient (Rmul)

       if(ABS(MSE) .gt. 1.0D-30)then
         F = MSR/MSE
       else
         F = 0.0D0
       end if

       IF(Rmul2 .gt. 0.0D0)THEN
          Rmul = SQRT(Rmul2)
       ELSE
          Rmul = 0.0D0
       END IF

C    Calculate t-statistic and standard error for each coefficient

       DO 150 i = 1, Nparam
          IF(XTX(i,i)*MSE .gt. 1.0D-30)THEN
            s = SQRT(MSE * XTX(i,i))
            seb(i) = s
            t(i) = b(i)/s
          ELSE
            seb(i) = 0.0D0
            t(i) = 0.0D0
          END IF
150    CONTINUE

C    Calculate standard error for each value of Ytheor

       DO 180 i = 1, Nexp
          s1 = 0.0D0
          DO 170 j = 1, Nparam
             s = 0.0D0
             DO 160 k = 1, Nparam
                s = s + XTX(j,k) * X(i,k)
160          CONTINUE
             s1 = s1 + s * X(i,j)
170       CONTINUE
          if(MSE*s1 .le. 1.0D-30)then
            seYth(i) = 0.0D0
          else
            seYth(i) = SQRT(MSE*s1)
          end if
180    CONTINUE

C    Restore original values of Yexp and X

       DO 200 i = 1, Nexp
          s = 1.0D0/Wroots(i)
          Yexp(i) = Yexp(i) * s
          DO 190 j = 1, Nparam
             X(i,j) = X(i,j) * s
190        CONTINUE
200    CONTINUE



On Mon, 2 Dec 2002 james.metz@abbott.com wrote:

> Date: Mon, 2 Dec 2002 19:08:14 -0600
> From: james.metz@abbott.com
> To: chemistry@ccl.net
> Cc: james.metz@abbott.com
> Subject: CCL:constrained multiple linear regression
> 
> CCL,
> 
>         I am looking for software (preferably free or inexpensive, code is 
> OK) that will allow me to perform
> constrained multiple linear regression.  For example, I have an equation 
> of the form:
> 
>         Y = a*X1 + b*X2 + c*X3 + d
> 
>         where: Y is the dependent variable
>                   X1 - X3 are independent variables (more than 1)
>                 a, b, c are coefficients
>                         d is a constant
> 
>         I must be able to constrain the range of values for a, b, c, and d 
> during the fitting.
> 
>         Please note that programs such as JMP, KalediaGraph, GraphPad 
> Prism, and several other packages do 
> NOT allow the user to do this, especially for more than one independent 
> variable.
> 
>         Can someone suggest a program or code to do this?
> 
>         Thank you,
>         Jim Metz
> 
> 
> James T. Metz, Ph.D.
> Research Investigator Chemist
> 
> GPRD R46Y AP10-2
> Abbott Laboratories
> 100 Abbott Park Road
> Abbott Park, IL  60064-6100
> U.S.A.
> 
> Office (847) 936 - 0441
> FAX    (847) 935 - 0548
> 
> james.metz@abbott.com
> 

Jan K. Labanowski            |    phone: 614-292-9279,  FAX: 614-292-7168
Ohio Supercomputer Center    |    E-mail: jkl@ccl.net 
1224 Kinnear Rd,             |    http://www.ccl.net/~jkl
Columbus, OH 43212-1163      |    http://www.ccl.net/    http://asdn.net/




