for loop in mata

[lindsy ben]

Dear statalist members
I am new to Mata language, in the code below i simulate a VAR(2) using Stata and it works fine, does anyone know how to do the last part concerning the forvalues loop in Mata ,
the two equation for VAR(2) : y1 and y2 are simulated individually in STATA , in matrix form the values for y1 and y2 are derived as :
y=cons+A1*l.y+A2*l.2y+ u
where y is vector containing y1 and y2 / A1, A2 are matrices defined in Mata, l.y amd l2.y are lag 1 and lag2 of variables y1 and y2. and u is a vector of errors

clear all
local t = 1200
set obs 1200
gen t = _n
tsset t
forvalues i=1/2 {
gen y`i'=rnormal() in 1/2
}
matrix M = 2, 0
matrix V = (1, 0.5\ 0.5, 1 ) // covariance matrix of errors
drawnorm u1 u2 , n(1200) cov(V) means(M) // drawing bivariate normal errors
mata:
t=1200
cons = (0.1\0.3)
A1 = (0.6,-0.2\0.4,0.2)
A2 = (0.2,0.4\-0.1,0.1)
Sigma = (1,0.5\0.5,1)
y=st_data(.,"y1 y2")
u=st_data(.,"u1 u2")
end
forvalues i=3/`t' {
qui {
replace y1 = 0.1 + 0.6*l.y1 - 0.2*l.y2 + 0.2*l2.y1 + 0.4*l2.y2 + u1 in `i'
replace y2 = 0.3 + 0.4*l.y1 + 0.2*l.y2 - 0.1*l2.y1 + 0.1*l2.y2 + u2 in `i'
}
* equations under forvalues loop in matrix form are y= cons+A1*l.y+ A2*l.2y + u
}
drop in 1/200

THANKS

[John Mullahy]

Lindsy: An incrementing Mata loop would look something like this

local t=1200
mata
for ( i=3; i<=`t'; i++) {
 j=i
}
j
end

which gives this result

. local t=1200

. mata
------------------------------------------------- mata (type end to exit) -------------------------------------
: for ( i=3; i<=`t'; i++) {
>  j=i
> }

: j
  1200

: end

[lindsy ben]

thanks john feedback, I don't know how to get the increment(i) inside the matrices to update the vector y at each step in order to simulate VAR(2), for example
y1= known initial value
y2= known initial value
// get the rest values according to :
vector y= constant vector+ cons matrix A1*[L.y(i)]+ cons matrixA2*[l.y(i)] +vector u
i would like to write this part of code in Mata

  forvalues i=3/`t' {
                qui {
   replace y1 = 0.1 + 0.6*l.y1 - 0.2*l.y2 + 0.2*l2.y1 + 0.4*l2.y2 + u1 in `i'
   replace y2 = 0.3 + 0.4*l.y1 + 0.2*l.y2 - 0.1*l2.y1 + 0.1*l2.y2 + u2 in `i'
                   }            
 } 

when I applied john's suggestion I get an error message

. clear all
. local t = 1200
.  set obs 1200
number of observations (_N) was 0, now 1,200
.  gen t = _n
.  tsset t 
        time variable:  t, 1 to 1200
                delta:  1 unit
.  forvalues i=1/2 {
  2.   gen y`i'=rnormal() in 1/2
  3.    }  
(1,198 missing values generated)
(1,198 missing values generated)
. matrix M = 2, 0
. matrix V = (1, 0.5\ 0.5, 1 )  // covariance matrix of errors
. drawnorm u1 u2 , n(1200) cov(V) means(M)  // drawing bivariate normal errors
.  mata:
------------------------------------------------- mata (type end to exit) --------------------------
: cons = (0.1\0.3)

: A1 = (0.6,-0.2\0.4,0.2)

: A2 = (0.2,0.4\-0.1,0.1)

: Sigma = (1,0.5\0.5,1)

: y=st_data(.,"y1 y2")

: u=st_data(.,"u1 u2")

: for ( i=3; i<=`t'; i++) {
>  j=i
>  replace y1 = 0.1 + 0.6*l.y1 - 0.2*l.y2 + 0.2*l2.y1 + 0.4*l2.y2 + u1 in `i'
type mismatch:  exp.exp:  transmorphic found where struct expected
(3 lines skipped)
----------------------------------------------------------------------------------------------------
r(3000);

end of do-file

r(3000);

[lindsy ben]

the below code doesn't work either, Could anyone please help me to get around this problem

clear all
local t = 1200
 set obs 1200
 gen t = _n
 tsset t 
 forvalues i=1/2 {
  gen y`i'=rnormal() in 1/2
   }  
  g y1_1=l.y1
  g y1_2=l2.y1
  g y2_1=l.y2
  g y2_2=l2.y2

matrix M = 2, 0
matrix V = (1, 0.5\ 0.5, 1 )  // covariance matrix of errors
drawnorm u1 u2 , n(1200) cov(V) means(M)  // drawing bivariate normal errors
 mata:
cons = (0.1\0.3)
A1 = (0.6,-0.2\0.4,0.2)
A2 = (0.2,0.4\-0.1,0.1)
Sigma = (1,0.5\0.5,1)
y=st_data(.,"y1 y2")
u=st_data(.,"u1 u2")
y11=st_data(.," y1_1 y2_1")
y22=st_data(.," y1_2 y2_2")
for ( i=3; i<=`t'; i++) {
y= cons+ A1*y11+ A2*y22+ u 
}
end

[John Mullahy]

I don't understand the objective of the program but when I ran your code in #4 I checked for conformability. A1 and A2 are 2x2 while y11 and y22 are 1200x2 before entering the Mata for loop. Your code in #3 uses the Stata command replace inside the Mata environment. You can issue a Stata command from inside Mata by using Mata's stata(...) function.