I got it.
This maybe useful for the beginner.
Thanks.
*====== RASing a Matrix ======
*Contributed by [[tom@mpsge.org|Tom Rutherford]] to the [[http://
www.gams.com/maillist/gams_l.htm|GAMS-User List]]: A recent request to
the GAMS group asked for code samples for RASing a matrix. Below is a
standalone program that (in this case) RASes a consumption flows
matrix. With appropriate modifications, it can be used for square
matrices (IO tables or SAMs) as well. I use it frequently for matrices
up to 30x30 without any difficulty at all.
$TITLE PROGRAM TO CARRY OUT RAS OF CONSUMPTION SHARES
$OFFSYMLIST OFFSYMXREF OFFUPPER
- Program requires specification of row and column indices
- If square matrix, only one set need be provided,
- and ALIAS statements changed
SETS
I SECTORS / FarmFood Farm Food Crops
Nonfood Farm Nonfood Crops
Livestck Livestock
Forestry Forestry
Fishery Fishery
OilGas Coal Gas & Oil
OthMines Other Mining
Foodproc Food Bev & Tobacco
Textiles Textiles & Leather
WoodFurn Wood & Furniture
PapPrint Paper & Printing
ChemRef Chemicals & Fertilizers
RefinLNG Refining LNG & Coal
Nometmin Nonmetallic Mineral
BasicMet Basic Metals
Machines Metal Prod & Machines
OthIndus Other Industry
Utility Elect Gas & Water
Construc Construction
TradStor Trade & Storage
RestHot Restaurants & Hotels
LandTran Rail & Road Transpor
OthTrans Sea Air Trans & Comm
FinServ Financial Serv & Insur
BusServ Real Estate
PubAdmin Public Admin
OthServ Social & Other Serv/,
HH HOUSEHOLD TYPE / rurwork Ag worker households
rurcap Ag owners households
urbwork Low wage households
urbcap High wage households/
YR IO year / 2005
2010/
;
- Program requires three different data inputs:
- CONFLOW: the matrix of original flows
- C0: column containing row sum controls
- CON: column containing column sum controls
TABLE CONFLOW1(yr,i,hh) INITIAL PRIVATE CONSUMPTION FLOWS
rurwork rurcap urbwork urbcap
2005.FarmFood 165.56 5356.08 1331.07 2757.31
2005.Nonfood 149.77 410.60 154.18 357.37
2005.Livestck 141.53 905.99 501.23 1904.72
2005.Forestry 56.70 141.65 55.69 56.52
2005.Fishery 170.94 849.68 394.32 932.19
2005.OilGas .00 .00 .00 .00
2005.OthMines .22 .86 .29 .56
2005.Foodproc 1169.48 5245.54 2777.09 6066.52
2005.Textiles 82.61 529.25 279.48 806.17
2005.Woodfurn 18.70 125.78 63.12 249.40
2005.PapPrint 5.10 54.76 33.10 151.39
2005.ChemRef 47.13 432.05 299.22 844.25
2005.RefinLNG 56.26 515.80 357.23 1007.92
2005.Nometmin 2.33 21.38 14.80 41.75
2005.BasicMet .00 .00 .00 .00
2005.Machines 44.89 481.86 291.23 1332.10
2005.OthIndus 3.67 39.38 23.80 108.85
2005.Utility 5.63 51.97 119.31 413.36
2005.Construc .00 .00 .00 .00
2005.TradStor 3.20 18.64 39.30 113.54
2005.RestHot 108.44 1045.05 1061.97 2564.35
2005.LandTran 42.85 313.51 600.14 1737.71
2005.OthTrans 13.25 147.42 277.10 994.59
2005.FinServ 23.17 300.03 136.31 589.15
2005.BusServ 87.98 779.65 700.31 1979.36
2005.PubAdmin .00 .00 .00 .00
2005.OthServ 116.65 853.46 987.11 4353.09
2010.FarmFood 165.56 5356.08 1331.07 2757.31
2010.Nonfood 149.77 410.60 154.18 357.37
2010.Livestck 141.53 905.99 501.23 1904.72
2010.Forestry 56.70 141.65 55.69 56.52
2010.Fishery 170.94 849.68 394.32 932.19
2010.OilGas .00 .00 .00 .00
2010.OthMines .22 .86 .29 .56
2010.Foodproc 1169.48 5245.54 2777.09 6066.52
2010.Textiles 82.61 529.25 279.48 806.17
2010.Woodfurn 18.70 125.78 63.12 249.40
2010.PapPrint 5.10 54.76 33.10 151.39
2010.ChemRef 47.13 432.05 299.22 844.25
2010.RefinLNG 56.26 515.80 357.23 1007.92
2010.Nometmin 2.33 21.38 14.80 41.75
2010.BasicMet .00 .00 .00 .00
2010.Machines 44.89 481.86 291.23 1332.10
2010.OthIndus 3.67 39.38 23.80 108.85
2010.Utility 5.63 51.97 119.31 413.36
2010.Construc .00 .00 .00 .00
2010.TradStor 3.20 18.64 39.30 113.54
2010.RestHot 108.44 1045.05 1061.97 2564.35
2010.LandTran 42.85 313.51 600.14 1737.71
2010.OthTrans 13.25 147.42 277.10 994.59
2010.FinServ 23.17 300.03 136.31 589.15
2010.BusServ 87.98 779.65 700.31 1979.36
2010.PubAdmin .00 .00 .00 .00
2010.OthServ 116.65 853.46 987.11 4353.09
;
PARAMETER c01(yr,i) Control vector ;
c01(“2005”,“FarmFood”) = 6394.42 ;
c01(“2005”,“Nonfood”) = 990.61 ;
c01(“2005”,“Livestck”) = 2661.24 ;
c01(“2005”,“Forestry”) = 259.31 ;
c01(“2005”,“Fishery”) = 1569.93 ;
c01(“2005”,“OilGas”) = .00 ;
c01(“2005”,“OthMines”) = .21 ;
c01(“2005”,“Foodproc”) =13911.94 ;
c01(“2005”,“Textiles”) = 1367.44 ;
c01(“2005”,“Woodfurn”) = 329.88 ;
c01(“2005”,“PapPrint”) = 161.59 ;
c01(“2005”,“ChemRef”) = 1160.43 ;
c01(“2005”,“RefinLNG”) = 1385.44 ;
c01(“2005”,“Nometmin”) = 57.41 ;
c01(“2005”,“BasicMet”) = .00 ;
c01(“2005”,“Machines”) = 1419.86 ;
c01(“2005”,“OthIndus”)= 116.05 ;
c01(“2005”,“Utility”) = 523.35 ;
c01(“2005”,“Construc”)= .00 ;
c01(“2005”,“TradStor”)= 5737.68 ;
c01(“2005”,“RestHot”) = 4553.91 ;
c01(“2005”,“LandTran”)= 3552.82 ;
c01(“2005”,“OthTrans”)= 1607.77 ;
c01(“2005”,“FinServ”) = 883.65 ;
c01(“2005”,“BusServ”) = 3287.49 ;
c01(“2005”,“PubAdmin”)= .00 ;
c01(“2005”,“OthServ”) = 9063.46 ;
c01(“2010”,“FarmFood”) = 6394.42 ;
c01(“2010”,“Nonfood”) = 990.61 ;
c01(“2010”,“Livestck”) = 2661.24 ;
c01(“2010”,“Forestry”) = 259.31 ;
c01(“2010”,“Fishery”) = 1569.93 ;
c01(“2010”,“OilGas”) = .00 ;
c01(“2010”,“OthMines”) = .21 ;
c01(“2010”,“Foodproc”) =13911.94 ;
c01(“2010”,“Textiles”) = 1367.44 ;
c01(“2010”,“Woodfurn”) = 329.88 ;
c01(“2010”,“PapPrint”) = 161.59 ;
c01(“2010”,“ChemRef”) = 1160.43 ;
c01(“2010”,“RefinLNG”) = 1385.44 ;
c01(“2010”,“Nometmin”) = 57.41 ;
c01(“2010”,“BasicMet”) = .00 ;
c01(“2010”,“Machines”) = 1419.86 ;
c01(“2010”,“OthIndus”)= 116.05 ;
c01(“2010”,“Utility”) = 523.35 ;
c01(“2010”,“Construc”)= .00 ;
c01(“2010”,“TradStor”)= 5737.68 ;
c01(“2010”,“RestHot”) = 4553.91 ;
c01(“2010”,“LandTran”)= 3552.82 ;
c01(“2010”,“OthTrans”)= 1607.77 ;
c01(“2010”,“FinServ”) = 883.65 ;
c01(“2010”,“BusServ”) = 3287.49 ;
c01(“2010”,“PubAdmin”)= .00 ;
c01(“2010”,“OthServ”) = 9063.46 ;
PARAMETER CON1(yr,hh) AGGREGATE CONSUMPTION LEVELS ;
CON1(“2005”,“rurwork”) = 2516.05 ;
CON1(“2005”,“rurcap”) = 18620.37 ;
CON1(“2005”,“urbwork”) = 10497.40 ;
CON1(“2005”,“urbcap”) = 29362.18 ;
CON1(“2010”,“rurwork”) = 2516.05 ;
CON1(“2010”,“rurcap”) = 18620.37 ;
CON1(“2010”,“urbwork”) = 10497.40 ;
CON1(“2010”,“urbcap”) = 29362.18 ;
PARAMETER CONFLOW(i,hh) INITIAL PRIVATE CONSUMPTION FLOWS;
PARAMETER c0(i) Control vector ;
PARAMETER CON(hh) AGGREGATE CONSUMPTION LEVELS ;
ALIAS(I,RR) ;
ALIAS(HH,CC) ;
PARAMETER a0(rr,cc) Initial coefficients matrix to RAS
a1(rr,cc) Final coefficients matrix after RAS
rasmat0(rr,cc) Initial flows matrix to RAS
ct(cc) RAS column control totals
rt(rr) RAS row control totals
ratio Adjustment parameter on control totals
checkcol Check sum of column control totals
checkrow Check sum of row control totals
sumccc Original column sums of RAS matrix
sumrrr Original row sums of RAS matrix
;
VARIABLES
DEV Deviations
RASMAT(rr,cc) RASed matrix
R1(rr) Rho of RAS matrix
S1(cc) Sigma of RAS matrix
LOSS Objective (loss) function value
;
EQUATIONS
BIPROP(rr,cc) Bi-proportionality for RAS matrix
DEVSQ Definition of squared deviations
OBJ Objective function
RCONST(rr) Row constraint
CCONST(cc) Column constraint
;
BIPROP(rr,cc)… RASMAT(rr,cc) =E= R1(rr)*S1(cc)*rasmat0(rr,cc) ;
CCONST(cc)… ct(cc) =E= SUM(rr, RASMAT(rr,cc)) ;
RCONST(rr)… rt(rr) =E= SUM(cc, RASMAT(rr,cc)) ;
DEVSQ… DEV =E= SUM( (rr,cc)$rasmat0(rr,cc),
SQR( (RASMAT(rr,cc) - rasmat0(rr,cc)) /
rasmat0(rr,cc)) ) ;
OBJ… LOSS =E= SUM(rr, R1(rr)**2 + (1/R1(rr))**2 )
- SUM(cc, S1(cc)**2 + (1/S1(cc))**2 ) ;
MODEL CONSUMERAS / BIPROP
CCONST
RCONST
OBJ / ;
loop(yr,
conflow(rr,cc) = conflow1(yr,rr,cc);
c0(rr) = c01(yr,rr);
CON(cc) = CON1(yr,cc) ;
-
Parameter initialization
sumccc(cc) = SUM(rr, conflow(rr,cc) ) ;
sumrrr(rr) = SUM(cc, conflow(rr,cc) ) ;
a0(rr,cc) = conflow(rr,cc) / sumccc(cc) ;
rasmat0(rr,cc) = a0(rr,cc) * CON(cc) ;
ct(cc) = CON(cc) ;
rt(rr) = c0(rr) ;
ratio = SUM(rr, rt(rr)) / SUM(cc, ct(cc)) ;
ct(cc) = ct(cc) * ratio ;
checkcol = SUM(cc, ct(cc) );
checkrow = SUM(rr, rt(rr) );
*display sce_1, ratio, checkcol, checkrow ;
display ratio, checkcol, checkrow ;
display conflow, a0 ;
display con, ct ;
display c0, rt ;
-
Variable initialization
DEV.L = 0.0 ;
R1.L(rr) = 1 ;
S1.L(cc) = 1 ;
RASMAT.L(rr,cc) = a0(rr,cc) * ct(cc) ;
CON(cc) = ct(cc) ;
-
Variable bounds
RASMAT.LO(rr,cc) = 0.0 ;
R1.LO(rr) = 0.01 ;
S1.LO(cc) = 0.01 ;
*DEVSQ is commented out
OPTIONS ITERLIM=10000,LIMROW=0,LIMCOL=0,SOLPRINT=OFF ;
SOLVE CONSUMERAS USING NLP MINIMIZING LOSS ;
display rasmat.l, r1.l, s1.l ;
a1(rr,cc) = rasmat.l(rr,cc) / ct(cc) ;
display a0, a1 ;
) ;
On Oct 23, 11:58 pm, Pongsak Suttinon
wrote:
Hi Renger,
Thank you very much. I will try the other ways for this.
Regards,
Pongsak
On Fri, Oct 22, 2010 at 11:10 PM, Renger van Nieuwkoop >
rvannieuwk...@gmail.com> wrote:
Hi Pongsak
As Gams tells you in the error report, you can not define equations or
declare variables within a loop. Therefore, if you want to do this, you have
to put the declarations and definitions before the loop starts (the
equations themselves remain in the loop).
Renger
On Fri, Oct 22, 2010 at 1:39 PM, Pongsak Suttinon > > > pongsak.sutti...@gmail.com> wrote:
Now I am studying how to use GAMs in macro-economic. I found one
interesting example by Prof. Tom Rutherford about “RASting a Matrixâ€.
His example is showed in case of one table; however, I would like to
simulate the same process with the two or more tables. I tried to use
loop (while) but it shows errors as
169 Equation definition within a LOOP or IF statement not allowed
257 Solve statement not checked because of previous errors
349 Declaration not allowed inside a LOOP or IF statement
I would appreciate if you could help me in this topic.
Thank you very much.
Best regards,
Pongsak SUTTINON
Ps. The following code is the edited file with errors.
*====== RASing a Matrix ======
*Contributed by [[t…@mpsge.org|Tom Rutherford]] to the [[http://
www.gams.com/maillist/gams_l.htm|GAMS-UserList]]: A recent request to
the GAMS group asked for code samples for RASing a matrix. Below is a
standalone program that (in this case) RASes a consumption flows
matrix. With appropriate modifications, it can be used for square
matrices (IO tables or SAMs) as well. I use it frequently for matrices
up to 30x30 without any difficulty at all.
$TITLE PROGRAM TO CARRY OUT RAS OF CONSUMPTION SHARES
$OFFSYMLIST OFFSYMXREF OFFUPPER
- Program requires specification of row and column indices
- If square matrix, only one set need be provided,
- and ALIAS statements changed
SETS
I SECTORS / FarmFood Farm Food Crops
Nonfood Farm Nonfood Crops
Livestck Livestock
Forestry Forestry
Fishery Fishery
OilGas Coal Gas & Oil
OthMines Other Mining
Foodproc Food Bev & Tobacco
Textiles Textiles & Leather
WoodFurn Wood & Furniture
PapPrint Paper & Printing
ChemRef Chemicals & Fertilizers
RefinLNG Refining LNG & Coal
Nometmin Nonmetallic Mineral
BasicMet Basic Metals
Machines Metal Prod & Machines
OthIndus Other Industry
Utility Elect Gas & Water
Construc Construction
TradStor Trade & Storage
RestHot Restaurants & Hotels
LandTran Rail & Road Transpor
OthTrans Sea Air Trans & Comm
FinServ Financial Serv & Insur
BusServ Real Estate
PubAdmin Public Admin
OthServ Social & Other Serv/,
HH HOUSEHOLD TYPE / rurwork Ag worker households
rurcap Ag owners households
urbwork Low wage households
urbcap High wage households/
;
- Program requires three different data inputs:
- CONFLOW: the matrix of original flows
- C0: column containing row sum controls
- CON: column containing column sum controls
TABLE CONFLOW(i,hh) INITIAL PRIVATE CONSUMPTION FLOWS
rurwork rurcap urbwork urbcap
FarmFood 165.56 5356.08 1331.07 2757.31
Nonfood 149.77 410.60 154.18 357.37
Livestck 141.53 905.99 501.23 1904.72
Forestry 56.70 141.65 55.69 56.52
Fishery 170.94 849.68 394.32 932.19
OilGas .00 .00 .00 .00
OthMines .22 .86 .29 .56
Foodproc 1169.48 5245.54 2777.09 6066.52
Textiles 82.61 529.25 279.48 806.17
Woodfurn 18.70 125.78 63.12 249.40
PapPrint 5.10 54.76 33.10 151.39
ChemRef 47.13 432.05 299.22 844.25
RefinLNG 56.26 515.80 357.23 1007.92
Nometmin 2.33 21.38 14.80 41.75
BasicMet .00 .00 .00 .00
Machines 44.89 481.86 291.23 1332.10
OthIndus 3.67 39.38 23.80 108.85
Utility 5.63 51.97 119.31 413.36
Construc .00 .00 .00 .00
TradStor 3.20 18.64 39.30 113.54
RestHot 108.44 1045.05 1061.97 2564.35
LandTran 42.85 313.51 600.14 1737.71
OthTrans 13.25 147.42 277.10 994.59
FinServ 23.17 300.03 136.31 589.15
BusServ 87.98 779.65 700.31 1979.36
PubAdmin .00 .00 .00 .00
OthServ 116.65 853.46 987.11 4353.09
;
PARAMETER c0(i) Control vector ;
c0(“FarmFood”) = 6394.42 ;
c0(“Nonfood”) = 990.61 ;
c0(“Livestck”) = 2661.24 ;
c0(“Forestry”) = 259.31 ;
c0(“Fishery”) = 1569.93 ;
c0(“OilGas”) = .00 ;
c0(“OthMines”) = .21 ;
c0(“Foodproc”) =13911.94 ;
c0(“Textiles”) = 1367.44 ;
c0(“Woodfurn”) = 329.88 ;
c0(“PapPrint”) = 161.59 ;
c0(“ChemRef”) = 1160.43 ;
c0(“RefinLNG”) = 1385.44 ;
c0(“Nometmin”) = 57.41 ;
c0(“BasicMet”) = .00 ;
c0(“Machines”) = 1419.86 ;
c0(“OthIndus”)= 116.05 ;
c0(“Utility”) = 523.35 ;
c0(“Construc”)= .00 ;
c0(“TradStor”)= 5737.68 ;
c0(“RestHot”) = 4553.91 ;
c0(“LandTran”)= 3552.82 ;
c0(“OthTrans”)= 1607.77 ;
c0(“FinServ”) = 883.65 ;
c0(“BusServ”) = 3287.49 ;
c0(“PubAdmin”)= .00 ;
c0(“OthServ”) = 9063.46 ;
PARAMETER CON(hh) AGGREGATE CONSUMPTION LEVELS ;
CON(“rurwork”) = 2516.05 ;
CON(“rurcap”) = 18620.37 ;
CON(“urbwork”) = 10497.40 ;
CON(“urbcap”) = 29362.18 ;
ALIAS(I,RR) ;
ALIAS(HH,CC) ;
PARAMETER a0(rr,cc) Initial coefficients matrix to RAS
a1(rr,cc) Final coefficients matrix after RAS
rasmat0(rr,cc) Initial flows matrix to RAS
ct(cc) RAS column control totals
rt(rr) RAS row control totals
ratio Adjustment parameter on control totals
checkcol Check sum of column control totals
checkrow Check sum of row control totals
sumccc Original column sums of RAS matrix
sumrrr Original row sums of RAS matrix
;
VARIABLES
DEV Deviations
RASMAT(rr,cc) RASed matrix
R1(rr) Rho of RAS matrix
S1(cc) Sigma of RAS matrix
LOSS Objective (loss) function value
;
scalar sce_1 ; sce_1=1 ;
while((sce_1 le 2),
*$ontext
if (sce_1 = 1,
conflow(rr,cc) = conflow(rr,cc);
c0(rr) = c0(rr);
CON(cc) = CON(cc) ;
);
if (sce_1 = 2,
conflow(rr,cc) = conflow(rr,cc);
c0(rr) = 1.5c0(rr);
CON(cc) = 1.5CON(cc) ;
);
*$offtext
- Parameter initialization
sumccc(cc) = SUM(rr, conflow(rr,cc) ) ;
sumrrr(rr) = SUM(cc, conflow(rr,cc) ) ;
a0(rr,cc) = conflow(rr,cc) / sumccc(cc) ;
rasmat0(rr,cc) = a0(rr,cc) * CON(cc) ;
ct(cc) = CON(cc) ;
rt(rr) = c0(rr) ;
ratio = SUM(rr, rt(rr)) / SUM(cc, ct(cc)) ;
ct(cc) = ct(cc) * ratio ;
checkcol = SUM(cc, ct(cc) );
checkrow = SUM(rr, rt(rr) );
display sce_1, ratio, checkcol, checkrow ;
display conflow, a0 ;
display con, ct ;
display c0, rt ;
DEV.L = 0.0 ;
R1.L(rr) = 1 ;
S1.L(cc) = 1 ;
RASMAT.L(rr,cc) = a0(rr,cc) * ct(cc) ;
CON(cc) = ct(cc) ;
EQUATIONS
BIPROP(rr,cc) Bi-proportionality for RAS matrix
DEVSQ Definition of squared deviations
OBJ Objective function
RCONST(rr) Row constraint
CCONST(cc) Column constraint
;
BIPROP(rr,cc)… RASMAT(rr,cc) =E= R1(rr)*S1(cc)*rasmat0(rr,cc) ;
CCONST(cc)… ct(cc) =E= SUM(rr, RASMAT(rr,cc)) ;
RCONST(rr)… rt(rr) =E= SUM(cc, RASMAT(rr,cc)) ;
DEVSQ… DEV =E= SUM( (rr,cc)$rasmat0(rr,cc),
SQR( (RASMAT(rr,cc) - rasmat0(rr,cc)) /
rasmat0(rr,cc)) ) ;
OBJ… LOSS =E= SUM(rr, R1(rr)**2 + (1/R1(rr))**2 )
+ SUM(cc, S1(cc)**2 + (1/S1(cc))**2 ) ;
- Variable bounds
RASMAT.LO(rr,cc) = 0.0 ;
R1.LO(rr) = 0.01 ;
S1.LO(cc) = 0.01 ;
MODEL CONSUMERAS / BIPROP
CCONST
RCONST
-
DEVSQ
OBJ / ;
*DEVSQ is commented out
OPTIONS ITERLIM=10000,LIMROW=0,LIMCOL=0,SOLPRINT=OFF ;
SOLVE CONSUMERAS USING NLP MINIMIZING LOSS ;
display rasmat.l, r1.l, s1.l ;
a1(rr,cc) = rasmat.l(rr,cc) / ct(cc) ;
display a0, a1 ;
*
sce_1 = sce_1+1 ;
) ;
–
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