Hi there,

I’m still working on the restricted OLS regressions and in the meantime even uploaded an early version of a function package that uses a SQP of GNU R and a bootstrap routine to get coeffs and standard errors.

In order to produce a nice show case of the optimization problem I generate all combination of coefficients with a step size of n. If there are 3 coeffs that are >=0 and should sum up to 1 the matrix can be easily generated via loop. Since gretl has a special "for loop" one could use this loop version in order to fill the percentages in the matrix in one step. However, there is a bug. Have a look. I’m using the current x64 snapshot for windows.

Cheers and a nice first Sunday in Advent

Leon

<hansl>

scalar intN_1_a = 50 # step size of 2 percent

scalar intStep = 1/intN_1_a

eval intStep

matrix mCombis = NA

matrix mCombisALL = NA

set stopwatch

loop for i=0..intN_1_a --quiet

    loop for j=0..intN_1_a --quiet

        if i+j<=intN_1_a

            if i+j == 0

                mCombisALL = i ~ j ~ (intN_1_a-i-j)

            else   

                mCombisALL |= i ~ j ~ (intN_1_a-i-j)

            endif   

        endif  

    endloop 

endloop

eval $stopwatch/60

eval rows(mCombisALL)

# correct number of rows since

scalar intSum3 = (intN_1_a)*3 + (1+intN_1_a-3+1)*(1+intN_1_a-3)/2

# for three coeefs I found this closed formula, with more it’s another…

eval intSum3

set stopwatch

loop for (i=0; i<=1; i+=intStep) --quiet

    loop for (j=0; j<=1; j+=intStep) --quiet

        if i+j<=1

            if i+j == 0

                mCombis = i ~ j ~ (1-i-j)

            else   

                mCombis |= i ~ j ~ (1-i-j)

            endif   

        endif  

    endloop 

endloop

eval rows(mCombis)

eval $stopwatch

# correct number

scalar intSum3 = (intN_1_a)*3 + (1+intN_1_a-3+1)*(1+intN_1_a-3)/2

eval intSum3

# wrong, WHY? The reason has to do with the.xx999 values and the missing 1s.

<hansl>